Data Nerds! Super stoked to finally have this course launched!!...again (BTW, I have a FAQ👇) Quick background on this course: I first launched this last November, and unfortunately, shortly after that, a plug-in that I used for the course (i.e., Noteable) was deprecated, causing me to pause enrollment for the course while I fixed it. Additionally, this entire course was behind a paywall, and I’ll be honest, I didn’t feel right keeping video content from my subscribers. So I felt like this was a sign and instead decided to make the entire course public after I upgraded the course for the deprecated plug-in issues. So, I want to thank those who support the course by buying the course notes and certificate; without y’all, future tutorials wouldn’t be possible. ✌ FAQ === Q: How do I enable 'Advanced Data Analysis', it's not in Settings under "Beta Features"? A: 18:30 ADA is no longer included under this section and is auto included in the most advanced model. Q: Does this require a ChatGPT subscription? A: Yes, you’ll need a Plus or Enterprise subscription to unlock the full potential of ChatGPT. The free version of ChatGPT is not powerful enough for this course. Q: Do I need to know how to code to take this course? A: No prior coding or analytical experience is required! This is for data professionals who want to automate finding data insights. Q: What are the computer requirements? A: You only need a functioning laptop, desktop, or tablet with an internet connection; we’ll access everything through a web browser, from ChatGPT to the course material.
This is amazing. Thank you so much. Please can you start a Patreon or something so we can support you on a regular basis. I have also purchased your course. 😄
this is incredible. Thank you so much for taking the time to make this and providing it to us. This is 100% exactly what I need on the exact weekend I needed it. I promise once I get a job I'll find a way to thank you with more than a nice comment. You are AWESOME!
Luke, I don't usually comment on youtuve videos but I think this time is worth it. Thank you for creating this course. I am a physician deeping into data analysis and statistics for my job as a researcher. Thank you.
Luke ! My Luke ! You are making my life way easier. I am looking for a long time now for somebody to help me start the journey of data analytics and I have to say that since I came onto your channel, I left the Gray area. Thank you for all that you do ! Thank you that for making everything understandable ! Thank you !
🎯 Key Takeaways for quick navigation: 00:00 💡 *Introduction to ChatGPT for Data Analytics* - The video introduces ChatGPT as a tool for data analytics, highlighting its time-saving benefits and versatile applications in tasks ranging from spreadsheet analysis to advanced machine learning. 00:27 📘 *Course Overview* - The tutorial is structured into six chapters, covering ChatGPT setup, basic and advanced prompting techniques, plugins, data collection methods, and how to use ChatGPT for data analytics effectively. 01:09 🛠️ *ChatGPT Features and Plugins* - Focus on Advanced Data analysis, gpts (customized ChatGPT models), and plugins for browsing the internet and image generation. 01:22 🌐 *Data Collection Techniques* - Emphasizes the importance of data collection, including finding public datasets and web scraping methods. 02:03 📊 *Efficiency and Quality Improvement with ChatGPT* - A Harvard study showed ChatGPT users complete tasks 25% faster with a 40% increase in quality, illustrating the efficiency and effectiveness of using ChatGPT in data analytics. 02:31 💼 *ChatGPT Plus for Advanced Capabilities* - Discusses the necessity of ChatGPT Plus for access to advanced features like data analysis and internet browsing, especially for individual users. 03:25 🏢 *ChatGPT for Businesses* - Explains options for businesses, such as Enterprise and Team editions of ChatGPT, which are suitable for handling secure and confidential data. 05:01 🔑 *Setting Up ChatGPT Plus* - Guides through the process of signing up and upgrading to ChatGPT Plus, ensuring access to the latest model and features necessary for the course. 06:53 🤖 *Exploring ChatGPT Interface* - Provides an overview of ChatGPT's layout, including the sidebar, chat history, settings, and accessing custom-built models (gpts) for specific functions. 07:07 🎛️ *Layout Changes in ChatGPT* - Addresses recent layout changes in ChatGPT and ensures consistency in the course content with the current interface. 09:00 🌟 *Utilizing ChatGPT's Capabilities* - Demonstrates basic prompting techniques and how to maximize ChatGPT's capabilities for efficient and accurate responses. 11:18 💬 *Developing Personal Context Statements* - Encourages creating personal context statements to guide ChatGPT in providing tailored and relevant responses. 12:12 🔄 *Updating ChatGPT's Knowledge* - Discusses ChatGPT's knowledge level and the importance of using the internet browsing feature for up-to-date information. 14:03 🤹♂️ *Mastering Prompting Techniques* - Focuses on improving prompting techniques with context and task considerations to get precise and desired results from ChatGPT. 16:33 ⚙️ *Setting Up Custom Instructions* - Demonstrates how to set up custom instructions in ChatGPT for personalized and efficient use, aligning with individual preferences and requirements. 17:45 🔧 *Customizing ChatGPT Responses* - ChatGPT's custom instructions can be tailored for specific formats and tones in responses, including the use of emojis and concise answers, ensuring each new chat session starts with these preferences loaded. 18:26 🌓 *Setting Preferences in ChatGPT* - Users can adjust settings like themes (dark or light mode), clear chat history, and enable beta features like plugins and Advanced Data analysis for enhanced functionality. 19:07 🔒 *Data Security and Privacy Settings* - ChatGPT Plus may not be secure for confidential or proprietary data, suggesting the use of ChatGPT Enterprise for handling sensitive information, which is SOC 2 compliant. 20:43 👁️ *ChatGPT's Image Analysis Capability* - ChatGPT can now analyze images, offering a unique application in data analytics by interpreting graphs, visualizations, and data models from uploaded images. 26:46 📊 *Introduction to Advanced Data Analysis Plugin* - The Advanced Data Analysis plugin in ChatGPT is a powerful tool for exploring data sets, performing statistics, exploratory data analysis, and machine learning predictions. 29:03 ⏳ *Handling Timeouts in Data Analysis Sessions* - ChatGPT's environment may time out during advanced data analysis sessions, requiring users to re-upload files for continued analysis without losing previous work. 31:08 🔄 *Transitioning Between ChatGPT Models* - Users should ensure they use the ChatGPT model with Advanced Data Analysis enabled for complex data analytics tasks, as base models without this feature may produce inaccurate results. 36:02 💻 *Advanced Data Analysis Execution in ChatGPT* - ChatGPT's Advanced Data Analysis feature executes Python code directly within the chat interface, allowing users to see and verify the accuracy of calculations in real-time. 36:57 📈 *Versatility of Advanced Data Analysis* - The Advanced Data Analysis feature can handle a wide range of tasks including data processing, statistical analysis, predictive modeling, and custom queries, making it a robust tool for data analysts. 38:03 📊 *File Type Flexibility in Data Analysis* - ChatGPT accepts a variety of file types for data analysis, including CSV, Excel, Json, and more, demonstrating its flexibility in handling different data formats. 41:16 📊 *Descriptive and Exploratory Data Analysis* - ChatGPT can perform descriptive statistics and exploratory data analysis (EDA) on datasets, providing insights through visualizations like histograms and bar charts. 46:06 🧹 *Importance of Data Cleanup in Analysis* - Effective data analysis often requires cleaning up datasets, such as removing unnecessary spaces or renaming columns, to ensure accurate categorization and analysis. 48:08 📉 *Complex Data Visualization Techniques* - Advanced visualizations, such as analyzing salary data in relation to job platforms, job titles, and locations, can provide deeper insights and identify trends within datasets. 52:29 🤖 *Machine Learning Predictions with ChatGPT* - ChatGPT can build machine learning models, like Random Forest, to predict data such as yearly salaries, using inputs like job titles, platforms, and locations. 55:36 📉 *Understanding Model Error Metrics* - The Root Mean Square Error (RMSE) metric is used to evaluate the model's accuracy, indicating an average deviation of about $22,000 from actual yearly salaries, which is crucial for gauging the model's performance. 56:30 💹 *Testing the Predictive Model* - Testing the machine learning model with real-world scenarios, like predicting salaries for specific job titles and platforms, demonstrates its practical application and allows comparison with external salary data sources like Glassdoor. 58:06 📊 *Model Performance Variability* - The predictive accuracy varies across different roles, with senior roles showing more accurate predictions. This variability highlights the importance of having a well-defined and diverse dataset for training. 59:42 🌐 *Internet Access Limitation* - Advanced Data Analysis in ChatGPT cannot directly connect to online data sources like databases or APIs, which limits its ability to directly analyze data from the internet. 01:00:24 📊 *File Size Limitation* 01:01:58 🔒 *Security Concerns* 01:15:10 📈 *Visualization Tasks* 01:17:03 📝 *Visualization Task Recap* 01:19:20 📊 *Histogram and Box Plot Analysis* 01:27:16 📈 *Visualization Best Practices* 01:33:38 🖼️ *Clutter-Free Visuals* 01:34:34 🎨 *Focused Attention* 01:35:42 📊 *Effective Communication* 01:38:02 📈 *Visualization Improvement Task* 01:38:42 🔢 *Basic Statistics: Numerical Data* 01:46:13 🔠 *Basic Statistics: Categorical Data* 01:50:34 📊 *Four Types of Data Analytics* 01:52:22 🔍 *Diagnostic Analytics* 01:53:16 🔮 *Predictive Analytics* 01:54:07 📊 *Prescriptive Analytics* 01:56:26 📈 *Descriptive Analytics* 01:59:15 🧐 *Deep Dive into Diagnostic Analytics* 02:06:09 🤖 *Building Predictive Models* 02:09:26 🧠 *Advanced Prescriptive Analytics* 02:11:44 📊 *Recommender Algorithm for Data Analysts* 02:13:10 🧠 *Advanced ChatGPT Topics* 02:14:03 🤖 *Understanding ChatGPT's Token Limit* 02:15:28 🚫 *Hallucinations and Bias in ChatGPT* 02:16:24 🌡️ *Exploring ChatGPT's Temperature Setting* 02:18:27 📚 *Case Study on ChatGPT's Hallucinations* 02:30:03 📝 *Format and Tone in Custom Instructions* 02:33:21 📊 *Custom Instructions for Optimized Responses* 02:39:25 🤖 *Building Custom GPTs for Specific Tasks* 02:47:00 🛠️ *Importance of Refining Custom GPTs* 02:47:13 🛠️ *Creating a Personalized GPT* 02:47:42 🔌 *Intro to ChatGPT Plugins* 02:58:44 🌐 *Browsing the Internet with ChatGPT* 03:03:44 📊 *Using Wolfram Plugin for Analytics* 03:04:39 🧮 *Wolfram Plugin for Data Analysis* 03:08:17 🖼️ *DALL-E 3 Plugin for Image Generation* 03:13:33 📊 *Introduction to Data Collection Methods* 03:17:10 🌐 *Resources for Finding Public Data Sets* 03:21:09 🕸️ *Intro to Web Scraping with ChatGPT* 03:22:56 ⚖️ *Legal Considerations in Web Scraping* 03:24:33 📂 *Legally Collecting Data from Websites* 03:29:22 🌐 *Using ChatGPT for Data Extraction* 03:30:27 🛠️ *Advanced Concepts in Web Scraping* 03:32:19 🤖 *Checking Website Legality for Scraping* Made with HARPA AI
Completed this course and it really inspired me to delve deeper into ChatGPT and data analysis. The course is really comprehensive, explains the topics well and has active examples which you can follow along with. I managed to get lost a couple of times, but learnt heaps finding my way back - really builds confidence playing with a experimental dataset! One thing that confused me a little bit is that the dataset Luke uses for the course is a little older than the one that downloads, so the results are a little different.
Hello, I am a student and have questions about the process. I normally drop unwanted features, rename the column, fix the data type, and then clean the dataset by handling the duplicate and missing values. I made sure the data was clean before performing EDA, and other statistics. Is this the correct order?
@LukeBarousse dear sir thanks for creating a valuable content to be data analyst for us, but you are missing two topics related to data analyst 1- Statistics and mathematics 2- Power BI/Tableau Power BI is preferred bcz its similar to Excel
Hi Luke , i am having 10 years of experience as a Quality analyst in banking,can you please help me to suggest if self-study or doing a master's is a good option
Hi , i am having 10 years of experience as a Quality analyst in banking,can you please help me to suggest if self-study or doing a master's is a good option for data science
Thank you for this video. Can you please do a video on using Gemini Advanced for Data Analytics? I curious as to how it would perform compared to Chatgpt 4.
I have ChatGPT 4 and in settings for Beta Features, I only have the option to enable plugins and not the Advanced Data Analyst. What should I do to enable this beta features? Reference @ 18:34
I took the course (which was great btw) and was very excited to create a custom GPT. I uploaded three CSV files to use as knowledge data. I provided the key column for each relationship. There are a Company file, statistical question file and a statistical answer file (with two years of data). The experience was laughable. I instructed ChatGPT to only use the data I provided and it constantly made up responses. It even made up data as it was telling me HOW it was coming up with the FAKE responses. I would ask a question like "How many widgets did Acme Corp sell in 2023?" It would respond like "I see Acme Corp listed in the Company file and it is company 1234 (there was no company with that ID). I see the code for the widget question in the Stats Questions file is WDGT (that didn't exist) and the data in the Answers file linked by the question code. So Acme Corp sold 552 widgets (it made up that number)." I must have tried 25 different ways to tell it what is was doing wrong and it would sound like it "Got it" but it only gave me the correct answer once. When I changed the question, it screwed up in new ways. Has anyone had this type of experience?
Hello Luke, I had some issues generating the machine learning model. I tried and tried but chatgpt said " Error analyzing It seems I've encountered limitations that prevent executing machine learning model training, specifically with the Random Forest Regressor, directly in this environment. This limitation is related to the operational constraints of the platform rather than an issue with the code itself. Although I'm designed to assist with generating and explaining code, including machine learning models, the execution of certain tasks, especially those requiring extensive computational resources or specific library functions like scikit-learn, might exceed the capabilities provided here. For running complex machine learning models like the Random Forest Regressor, I recommend using a local Python environment or a dedicated data science platform. These environments offer the computational resources and library support needed for such tasks, allowing you to train, test, and deploy machine learning models effectively." Thank you for your help.
just got the course and wow! totally worth it. great job with all of the resources. I thought it was just a donation thing, but was surprised by how affordable it is. excited to start!
Great intro course but is there a way i can get more details into Predictive and Prescriptive Data analytics. Like, go more into details. I will gladly pay for such a course.
Hi Luke. I am completely new in this field. I always loved doing analyses in excel. But I found my self limited. Now I am going through your course of SQL and also went through this course. I was able to set up local LLM using LM Studio (on MacBook Air M2) and get it running in VS Code via Continue extension. My question is, have you tried some locally running LLM? Also I recently found Microsoft LIDA. It would be great if we have your opinion on this tools.
Silly question, I would love to do this kind of analysis with my job (not data analysis/nerd job more of a numbers nerd with a data bent) any sources I can go to find a similar for accounting-finance jobs?
Hi, Luke - ref. Settings: You advised to make sure we allow both Pluggins and ADA under Settings. However, my ChatGPT settings only show Pluggins, and not ADA (I refer to minute 34:47 of your clip). is there a problem with the Settings? What should I do? Thank you!
Hi thanks for the great course! After subscribing for ChatGPT Plus (20$/month), it seems the usage policy is limiting usage after about 20 messages. Any recommendation how to deal with this limitation? Thanks
I am planning to buy your course ChatGPT for Data Analytics. Is it okay to become a data analyst without knowing coding? Can I get a good job and salary? Can the company accept me to do data analysis with the chat gpt4? Please let me know.
Hello Luke. Great video as always. In yr view, how would you like to rate gpt + plus response's accuracy and reliability especially for data analysis and simple ML model result?
Hi Luke thank you for this awesome tutorial. It realy makes me happy! i have a question. I have followed the instructions, but chatgpt reponds it cannot build a model. In stead is responds a method to build a random forrest model with python etc. Has something changed of am i doing something wrong? thank you for a response. Joost (The Netherlands)
Thank you Luke for this incredibly helpful course but all plugins have been discontinued and even ADA isn't offered anymore although if you ask chaGPT about it, it will give you similar features of its data analysis although not necessarily all of the ones mentioned in your course.
My biggest problem with ChatGPT is the inability to save data which you may be compiling. There should be a option to save a certain about of numerical data to reuse in your next analysis session vs having to reload each time
Great course Luke! I was wondering if whenever I upload a dataset file into a GPT chat, then I close the chat, then I reopen the chat, will the dataset file disappear? When I reopen the chat, and enter a new prompt to display a chart, it instead shows the python code. I would have to reupload the dataset file in order for the prompt to work
Also sometimes whenever I reupload the dataset file (both as a zip and csv file), I get an error message saying that there was an issue extracting the contents from the file. How to resolve the issue?
You say that Harvard suggests an improvement with the use of ChatGPT; is this the same study you mentioned in a previous video, that included the stipulation 'if it is within the scope' of what ChatGPT/the data nerd can do? I just recall that it suggested that data nerds did worse if it was outside the scope and they used ChatGPT wrong - I'm wondering if there has been some improvement that means this isn't true any more?
I have the feeling that once I finish learning Python, it won't be useful anymore. This AI things grows quickly. Great curse. Really impressive! Thanks a lot, one of the best channel of UA-cam.
Hi Luke, I have been experiencing frequent and prolonged errors with ChatGPT’s inability to read Excel, CSV and other file types. Even very small datasets seem to be a problem. Do you know whether this problem also persists in the USA, I'm living in the Netherlands Has anyone else experienced this issue? I think this is a major shortcoming of a service for which you also have to pay monthly
Hey @LukeBarousse , been watching your channel for quite some time big fan! I am somewhat mid level data analyst, at my job I struggle to problem solve and how to solution when given tasks. I tend to get stuck when using excel. Any tips to help with this?
When I try to execute the model I get this response "there was an issue with executing the model due to system limitations. I recommend the following steps to run this machine learning pipeline locally." I have a local environment to run this in and even a Google Colab account, but I'm sure this would be a show stopper for the non-technical audience.
At minute 50:18, the prompt you use isnt working for me. ChatGPT says that it can't excecute due to limitations. Do you have any idea how I can fix this?
Hey master Luke, great opportunity this again. Can I ask, when you go to the link in the vid there are three vids with you can click on, it goes to the same page where you can pay to support you. Is it 3x 25$ or just one time? Love to support to keep up the great work you do
18:34. Why doesn't my "beta features" list include "advanced data analysis"? I only see "plugins". Is it possibly because I don't have extensive use of ChatGPT yet?
I'm constantly having to reupload the data. This makes going through this course a bit of pain when you can't go through the entire course in one sitting. Is this because I'm not using the Enterprise subscription? Or is this how it works regardless of subscription level.
I just asked ChatGPT about this and it's a limitation regardless your tier. But as mentioned in the video ChatGPT seems to retain the progress. Not sure how that makes sense though.
buddy thank you so much for teaching us so much on UA-cam. But... am I the only one having ONLY problem problem problem?! My ChatGPT (4, of course) only answers: i have a problem, i cannot perform this, i cannot perform that, I apologize, i have a technical problem, the problem is permanent, I am sorry but... That's it. Especially with the dataset you provided (which is way too big even to be opened on my excel...). If i use a smaller dataset "sometimes" i can see some elaboration and ChatGPT at least tryies to help as much as it can (few). Please consider i am copying and pasting your exact prompt. No way to work here. Just 20% of times, the rest is "i have a technical problem, i am sorry...." and "error analyzing". Frustrating is not enough. Is ChatGPT still working or not?!
I'm trying to connect to the data source (40:00) but the zip file is 60MB, so when I try to attach it to ChatGPT, the file exceeds the limit, even with Pro. It doesn't allow me to send the attachment, with the send button grayed out. Any fixes for this?
And one more question there is limit of 50 messages / 3 hour so that's very low limit, so how can you continue working with this even I have the pro version but still it's not worth enough because you cannot use it continuously because you there is a message cap limit.
*ChatGPT for Data Analytics: A Comprehensive Course Breakdown* *1⃣ Intro to ChatGPT (**0:00** - **26:37**)* * *0:00** Introduction:* This course teaches how to use ChatGPT for data analytics, showcasing its time-saving potential and applications. * *0:27** Course Overview:* The course is divided into six chapters covering ChatGPT setup, prompting, plugins, data collection, and data analysis. * *2:22** Options & Setup:* * *Free vs. Plus:* Free version is not suitable for the course; ChatGPT Plus is required for advanced features and costs $20 per month. * *Team vs. Enterprise:* Enterprise edition offers secure handling of sensitive data, ideal for businesses, while Team offers reduced features for smaller teams. * *Setup:* Signing up and upgrading to ChatGPT Plus is demonstrated. * *6:59** Walkthrough:* ChatGPT's interface is explored, covering the sidebar, chat history, settings, and access to custom-built models (GPTs). * *9:00** Utilizing ChatGPT's Capabilities:* Basic prompting techniques are demonstrated, emphasizing the importance of clear context and task definition for accurate results. * *11:18** Personal Context Statements:* Creating personal context statements to guide ChatGPT's responses is encouraged. * *12:12** Updating ChatGPT's Knowledge:* ChatGPT has a knowledge cut-off date (currently April 2023) and uses internet browsing for up-to-date information. * *14:03** Mastering Prompting Techniques:* Improving prompting with context and task considerations for better results. * *16:33** Setting Up Custom Instructions:* Setting up custom instructions for personalized and efficient use. * *20:43** ChatGPT's Image Analysis:* ChatGPT can analyze images, enabling interpretation of graphs and visualizations. *2⃣ Intro to Advanced Data Analysis (**26:38** - **1:01:57**)* * *26:38** Chapter Intro:* This chapter focuses on using ChatGPT's Advanced Data Analysis plugin for data exploration, statistics, and machine learning predictions. * *28:28** ADA Timeout Issues:* A temporary bug where Advanced Data Analysis sessions might time out, requiring re-uploading of files. * *30:00** ADA Intro:* Comparison between ChatGPT with and without Advanced Data Analysis, highlighting its significance for data tasks. * *36:02** Advanced Data Analysis Execution:* ChatGPT's Advanced Data Analysis feature executes Python code directly in the chat interface, allowing users to verify calculations. * *36:57** Versatility of Advanced Data Analysis:* The feature can handle various tasks, including data processing, statistical analysis, predictive modeling, and custom queries. * *38:03** File Type Flexibility:* ChatGPT accepts various file types for data analysis, including CSV, Excel, Json, and more. * *41:16** Descriptive & Exploratory Data Analysis:* ChatGPT performs descriptive statistics and exploratory data analysis (EDA), providing insights through visualizations. * *46:06** Importance of Data Cleanup:* Data cleanup is crucial for accurate analysis, including removing spaces or renaming columns. * *48:08** Complex Data Visualization:* Visualizations, such as analyzing salary data in relation to job platforms, titles, and locations, offer deeper insights. * *52:29** Machine Learning Predictions:* ChatGPT builds machine learning models, like Random Forest, to predict data, such as yearly salaries. * *55:36** Understanding Model Error Metrics:* Root Mean Square Error (RMSE) evaluates the model's accuracy, indicating the average deviation from actual salaries. * *56:30** Testing the Predictive Model:* Testing the model with real-world scenarios demonstrates its practical application. * *58:06** Model Performance Variability:* Predictive accuracy varies across different roles, highlighting the importance of a diverse dataset. * *59:42** Internet Access Limitation:* Advanced Data Analysis cannot directly connect to online data sources, limiting its ability to analyze internet data. * *1:00:24** File Size Limitation:* There's a 512MB file size limit for uploads to ChatGPT. * *1:01:58** Chapter Outro:* The chapter summarizes the importance of using Advanced Data Analysis for ad-hoc analysis and highlights the potential for future advancements. *3⃣ Basic Analysis (**1:03:27** - **2:09:04**)* * *1:03:27** Chapter Intro:* This chapter dives into basic visualizations and common statistics for those new to data analytics. * *1:07:11** Core Visualization:* Six common visualizations are explored: bar charts, line charts, pie charts, and scatter plots, with examples and use cases. * *1:16:32** Statistical Visualizations:* Histograms and box plots are examined for visualizing distributions and comparing data. * *1:27:16** Visualization Best Practices:* Recommendations for clutter-free visuals, focused attention, and effective communication with visualizations. * *1:38:02** Basic Statistics:* This section covers descriptive statistics for numerical and categorical data. * *1:50:34** Four Types of Data Analytics:* The four core types of data analytics are introduced: descriptive, diagnostic, predictive, and prescriptive. * *1:54:43** Descriptive Analysis:* Descriptive analysis focuses on understanding past data, using descriptive statistics and EDA. * *1:59:06** Diagnostic Analysis:* Diagnostic analysis explores the "why" behind observed trends, using drill-downs and further exploration of data. * *2:04:57** Predictive Analysis:* Predictive analysis uses past data to forecast future trends, often employing machine learning models. * *2:09:05** Prescriptive Analysis:* Prescriptive analysis provides recommendations for action based on predictions and insights. *4⃣ Advanced ChatGPT (**2:12:56** - **2:47:32**)* * *2:12:56** Chapter Intro:* This chapter focuses on mitigating hallucinations, mastering prompting techniques, and understanding GPTs (customized ChatGPT models). * *2:18:11** Hallucinations:* Hallucinations, where ChatGPT provides incorrect information, are explored with real-world examples and explanations. * *2:25:48** Prompting Best Practices:* A six-part prompt formula is introduced for improving ChatGPT's responses, including task, context, exemplar, persona, format, and tone. * *2:33:14** Custom Instructions:* Custom instructions are demonstrated as a method for automating context, format, and tone preferences in ChatGPT. * *2:39:01** GPTs:* GPTs, custom-built ChatGPT models, are explored with examples and instructions on building GPTs for specific tasks. * *2:47:13** Creating a Personalized GPT:* The importance of refining and improving custom GPTs for optimal results is emphasized. *5⃣ Intro to Plugins (**2:47:33** - **3:08:09**)* * *2:47:33** Chapter Intro:* This chapter introduces ChatGPT plugins for enhancing functionality and explores the benefits of using plugins for time-saving and automation. * *2:53:16** Browse with Bing:* Browsing the internet with ChatGPT is explored, highlighting its usefulness for retrieving up-to-date information. * *2:58:27** Time-Saver Plugins:* Various plugins are showcased for summarizing PDFs, web pages, articles, videos, and general knowledge. * *3:03:27** Wolfram Plugin:* The Wolfram plugin is explored for accessing a curated knowledge base of data, especially valuable for scientific and technical information. * *3:08:17** DALL-E 3 Plugin for Image Generation:* The DALL-E 3 plugin is introduced for generating images from text prompts, providing creative and visually appealing outputs. *6⃣ Data Collection (**3:13:18** - **3:33:48**)* * *3:13:18** Chapter Intro:* This chapter focuses on data collection methods, including finding public datasets, web scraping, and utilizing APIs. * *3:16:51** Public Data Sets:* Resources for finding public datasets are discussed, including Kaggle, GitHub, Reddit, and Google Dataset Search. * *3:20:58** Web Scraping Intro:* Web scraping is introduced as a method for extracting information from websites, emphasizing legal and ethical considerations. * *3:29:22** Using ChatGPT for Data Extraction:* An example of legally extracting data from Glassdoor job postings is demonstrated using ChatGPT's Advanced Data Analysis plugin. * *3:30:27** Advanced Concepts in Web Scraping:* A deeper dive into the legality of web scraping is provided, highlighting a landmark case involving LinkedIn and data scraping. * *3:32:19** Checking Website Legality for Scraping:* Methods for verifying whether a website allows scraping are discussed, including checking robots.txt files and terms of service. * *3:33:49** Course Wrap-up:* The course concludes with a reminder to complete the end-of-course survey to receive a certificate and further promotes the use of ChatGPT for data analysis. I used gemini-1.5-flash-latest to summarize the transcript. Cost (if I didn't use the free tier): $0.0072 Input tokens: 87318 Output tokens: 2043
Hey @jesus629, this is the same content from my course back in November, but packaged up into a single UA-cam video. The full course that you have has everything broken down into different segments for the chapters, making it easier to navigate and track. Nonetheless, you should have received an email a month ago asking if you'd like a refund for the course due to the deprecation of the "Noteable" plug-in. Hit me up via email if you want to go that route
Data Nerds! Super stoked to finally have this course launched!!...again (BTW, I have a FAQ👇)
Quick background on this course: I first launched this last November, and unfortunately, shortly after that, a plug-in that I used for the course (i.e., Noteable) was deprecated, causing me to pause enrollment for the course while I fixed it. Additionally, this entire course was behind a paywall, and I’ll be honest, I didn’t feel right keeping video content from my subscribers. So I felt like this was a sign and instead decided to make the entire course public after I upgraded the course for the deprecated plug-in issues. So, I want to thank those who support the course by buying the course notes and certificate; without y’all, future tutorials wouldn’t be possible. ✌
FAQ
===
Q: How do I enable 'Advanced Data Analysis', it's not in Settings under "Beta Features"?
A: 18:30 ADA is no longer included under this section and is auto included in the most advanced model.
Q: Does this require a ChatGPT subscription?
A: Yes, you’ll need a Plus or Enterprise subscription to unlock the full potential of ChatGPT. The free version of ChatGPT is not powerful enough for this course.
Q: Do I need to know how to code to take this course?
A: No prior coding or analytical experience is required! This is for data professionals who want to automate finding data insights.
Q: What are the computer requirements?
A: You only need a functioning laptop, desktop, or tablet with an internet connection; we’ll access everything through a web browser, from ChatGPT to the course material.
This is amazing. Thank you so much. Please can you start a Patreon or something so we can support you on a regular basis. I have also purchased your course. 😄
this is incredible. Thank you so much for taking the time to make this and providing it to us. This is 100% exactly what I need on the exact weekend I needed it. I promise once I get a job I'll find a way to thank you with more than a nice comment. You are AWESOME!
Luke, I don't usually comment on youtuve videos but I think this time is worth it. Thank you for creating this course. I am a physician deeping into data analysis and statistics for my job as a researcher. Thank you.
A really excellent course. Luke is energetic and articulate. He optimizes the use of GPT/ADA while at the same time telling you it is not perfect
I haven't even gotten very far yet but I'm blown away by the amount of your contribution to helping us out, thank you!
Luke ! My Luke ! You are making my life way easier. I am looking for a long time now for somebody to help me start the journey of data analytics and I have to say that since I came onto your channel, I left the Gray area.
Thank you for all that you do ! Thank you that for making everything understandable !
Thank you !
Glad to hear it!
I'm at a loss. Is there any point to learning SQL
🎯 Key Takeaways for quick navigation:
00:00 💡 *Introduction to ChatGPT for Data Analytics*
- The video introduces ChatGPT as a tool for data analytics, highlighting its time-saving benefits and versatile applications in tasks ranging from spreadsheet analysis to advanced machine learning.
00:27 📘 *Course Overview*
- The tutorial is structured into six chapters, covering ChatGPT setup, basic and advanced prompting techniques, plugins, data collection methods, and how to use ChatGPT for data analytics effectively.
01:09 🛠️ *ChatGPT Features and Plugins*
- Focus on Advanced Data analysis, gpts (customized ChatGPT models), and plugins for browsing the internet and image generation.
01:22 🌐 *Data Collection Techniques*
- Emphasizes the importance of data collection, including finding public datasets and web scraping methods.
02:03 📊 *Efficiency and Quality Improvement with ChatGPT*
- A Harvard study showed ChatGPT users complete tasks 25% faster with a 40% increase in quality, illustrating the efficiency and effectiveness of using ChatGPT in data analytics.
02:31 💼 *ChatGPT Plus for Advanced Capabilities*
- Discusses the necessity of ChatGPT Plus for access to advanced features like data analysis and internet browsing, especially for individual users.
03:25 🏢 *ChatGPT for Businesses*
- Explains options for businesses, such as Enterprise and Team editions of ChatGPT, which are suitable for handling secure and confidential data.
05:01 🔑 *Setting Up ChatGPT Plus*
- Guides through the process of signing up and upgrading to ChatGPT Plus, ensuring access to the latest model and features necessary for the course.
06:53 🤖 *Exploring ChatGPT Interface*
- Provides an overview of ChatGPT's layout, including the sidebar, chat history, settings, and accessing custom-built models (gpts) for specific functions.
07:07 🎛️ *Layout Changes in ChatGPT*
- Addresses recent layout changes in ChatGPT and ensures consistency in the course content with the current interface.
09:00 🌟 *Utilizing ChatGPT's Capabilities*
- Demonstrates basic prompting techniques and how to maximize ChatGPT's capabilities for efficient and accurate responses.
11:18 💬 *Developing Personal Context Statements*
- Encourages creating personal context statements to guide ChatGPT in providing tailored and relevant responses.
12:12 🔄 *Updating ChatGPT's Knowledge*
- Discusses ChatGPT's knowledge level and the importance of using the internet browsing feature for up-to-date information.
14:03 🤹♂️ *Mastering Prompting Techniques*
- Focuses on improving prompting techniques with context and task considerations to get precise and desired results from ChatGPT.
16:33 ⚙️ *Setting Up Custom Instructions*
- Demonstrates how to set up custom instructions in ChatGPT for personalized and efficient use, aligning with individual preferences and requirements.
17:45 🔧 *Customizing ChatGPT Responses*
- ChatGPT's custom instructions can be tailored for specific formats and tones in responses, including the use of emojis and concise answers, ensuring each new chat session starts with these preferences loaded.
18:26 🌓 *Setting Preferences in ChatGPT*
- Users can adjust settings like themes (dark or light mode), clear chat history, and enable beta features like plugins and Advanced Data analysis for enhanced functionality.
19:07 🔒 *Data Security and Privacy Settings*
- ChatGPT Plus may not be secure for confidential or proprietary data, suggesting the use of ChatGPT Enterprise for handling sensitive information, which is SOC 2 compliant.
20:43 👁️ *ChatGPT's Image Analysis Capability*
- ChatGPT can now analyze images, offering a unique application in data analytics by interpreting graphs, visualizations, and data models from uploaded images.
26:46 📊 *Introduction to Advanced Data Analysis Plugin*
- The Advanced Data Analysis plugin in ChatGPT is a powerful tool for exploring data sets, performing statistics, exploratory data analysis, and machine learning predictions.
29:03 ⏳ *Handling Timeouts in Data Analysis Sessions*
- ChatGPT's environment may time out during advanced data analysis sessions, requiring users to re-upload files for continued analysis without losing previous work.
31:08 🔄 *Transitioning Between ChatGPT Models*
- Users should ensure they use the ChatGPT model with Advanced Data Analysis enabled for complex data analytics tasks, as base models without this feature may produce inaccurate results.
36:02 💻 *Advanced Data Analysis Execution in ChatGPT*
- ChatGPT's Advanced Data Analysis feature executes Python code directly within the chat interface, allowing users to see and verify the accuracy of calculations in real-time.
36:57 📈 *Versatility of Advanced Data Analysis*
- The Advanced Data Analysis feature can handle a wide range of tasks including data processing, statistical analysis, predictive modeling, and custom queries, making it a robust tool for data analysts.
38:03 📊 *File Type Flexibility in Data Analysis*
- ChatGPT accepts a variety of file types for data analysis, including CSV, Excel, Json, and more, demonstrating its flexibility in handling different data formats.
41:16 📊 *Descriptive and Exploratory Data Analysis*
- ChatGPT can perform descriptive statistics and exploratory data analysis (EDA) on datasets, providing insights through visualizations like histograms and bar charts.
46:06 🧹 *Importance of Data Cleanup in Analysis*
- Effective data analysis often requires cleaning up datasets, such as removing unnecessary spaces or renaming columns, to ensure accurate categorization and analysis.
48:08 📉 *Complex Data Visualization Techniques*
- Advanced visualizations, such as analyzing salary data in relation to job platforms, job titles, and locations, can provide deeper insights and identify trends within datasets.
52:29 🤖 *Machine Learning Predictions with ChatGPT*
- ChatGPT can build machine learning models, like Random Forest, to predict data such as yearly salaries, using inputs like job titles, platforms, and locations.
55:36 📉 *Understanding Model Error Metrics*
- The Root Mean Square Error (RMSE) metric is used to evaluate the model's accuracy, indicating an average deviation of about $22,000 from actual yearly salaries, which is crucial for gauging the model's performance.
56:30 💹 *Testing the Predictive Model*
- Testing the machine learning model with real-world scenarios, like predicting salaries for specific job titles and platforms, demonstrates its practical application and allows comparison with external salary data sources like Glassdoor.
58:06 📊 *Model Performance Variability*
- The predictive accuracy varies across different roles, with senior roles showing more accurate predictions. This variability highlights the importance of having a well-defined and diverse dataset for training.
59:42 🌐 *Internet Access Limitation*
- Advanced Data Analysis in ChatGPT cannot directly connect to online data sources like databases or APIs, which limits its ability to directly analyze data from the internet.
01:00:24 📊 *File Size Limitation*
01:01:58 🔒 *Security Concerns*
01:15:10 📈 *Visualization Tasks*
01:17:03 📝 *Visualization Task Recap*
01:19:20 📊 *Histogram and Box Plot Analysis*
01:27:16 📈 *Visualization Best Practices*
01:33:38 🖼️ *Clutter-Free Visuals*
01:34:34 🎨 *Focused Attention*
01:35:42 📊 *Effective Communication*
01:38:02 📈 *Visualization Improvement Task*
01:38:42 🔢 *Basic Statistics: Numerical Data*
01:46:13 🔠 *Basic Statistics: Categorical Data*
01:50:34 📊 *Four Types of Data Analytics*
01:52:22 🔍 *Diagnostic Analytics*
01:53:16 🔮 *Predictive Analytics*
01:54:07 📊 *Prescriptive Analytics*
01:56:26 📈 *Descriptive Analytics*
01:59:15 🧐 *Deep Dive into Diagnostic Analytics*
02:06:09 🤖 *Building Predictive Models*
02:09:26 🧠 *Advanced Prescriptive Analytics*
02:11:44 📊 *Recommender Algorithm for Data Analysts*
02:13:10 🧠 *Advanced ChatGPT Topics*
02:14:03 🤖 *Understanding ChatGPT's Token Limit*
02:15:28 🚫 *Hallucinations and Bias in ChatGPT*
02:16:24 🌡️ *Exploring ChatGPT's Temperature Setting*
02:18:27 📚 *Case Study on ChatGPT's Hallucinations*
02:30:03 📝 *Format and Tone in Custom Instructions*
02:33:21 📊 *Custom Instructions for Optimized Responses*
02:39:25 🤖 *Building Custom GPTs for Specific Tasks*
02:47:00 🛠️ *Importance of Refining Custom GPTs*
02:47:13 🛠️ *Creating a Personalized GPT*
02:47:42 🔌 *Intro to ChatGPT Plugins*
02:58:44 🌐 *Browsing the Internet with ChatGPT*
03:03:44 📊 *Using Wolfram Plugin for Analytics*
03:04:39 🧮 *Wolfram Plugin for Data Analysis*
03:08:17 🖼️ *DALL-E 3 Plugin for Image Generation*
03:13:33 📊 *Introduction to Data Collection Methods*
03:17:10 🌐 *Resources for Finding Public Data Sets*
03:21:09 🕸️ *Intro to Web Scraping with ChatGPT*
03:22:56 ⚖️ *Legal Considerations in Web Scraping*
03:24:33 📂 *Legally Collecting Data from Websites*
03:29:22 🌐 *Using ChatGPT for Data Extraction*
03:30:27 🛠️ *Advanced Concepts in Web Scraping*
03:32:19 🤖 *Checking Website Legality for Scraping*
Made with HARPA AI
Thank you
Thank you Luke for all the support and amazing work you do to educate us. Keep up the good work and we here to support you
Just finished the course, a great one! Opened my eyes on chat GPT, will be using it now completely on a different level 🤩
Glad you enjoyed it!
Hi Luke, can you let me know what do you think about Google's course for data analytics?
Completed this course and it really inspired me to delve deeper into ChatGPT and data analysis. The course is really comprehensive, explains the topics well and has active examples which you can follow along with. I managed to get lost a couple of times, but learnt heaps finding my way back - really builds confidence playing with a experimental dataset!
One thing that confused me a little bit is that the dataset Luke uses for the course is a little older than the one that downloads, so the results are a little different.
Did this course on the train this morning, really good
Have not seen it yet, but I put "like" without any doubts - 3 hours of highly deliberated and structured content!
Hello, I am a student and have questions about the process. I normally drop unwanted features, rename the column, fix the data type, and then clean the dataset by handling the duplicate and missing values. I made sure the data was clean before performing EDA, and other statistics. Is this the correct order?
This is why I watch. Amazing useful quality content. Thanks so much Luke
No probs!
I’m going to complete this over the weekend.
Thank you for sharing all this knowledge!
Amazing to find this available on YT.
dude this is nuts! just got thru some of this content - can't believe its free! amazing video!
Glad you enjoy it!
Putting this thing on my learning wishlish. Really Helpful content❤
Thank you very much Mr. Luke from Iraq 🇮🇶 🙏
Seems to be some problem with the linked data file. ChatGPT hasn’t succeeded at analyzing it for me yet
@LukeBarousse dear sir thanks for creating a valuable content to be data analyst for us, but you are missing two topics related to data analyst
1- Statistics and mathematics
2- Power BI/Tableau
Power BI is preferred bcz its similar to Excel
please bring a full course about these topics from beginner to advanced as other topics
Hi Luke , i am having 10 years of experience as a Quality analyst in banking,can you please help me to suggest if self-study or doing a master's is a good option
1 question... Can we write off expenses related to professional appeaeance?
Hi , i am having 10 years of experience as a Quality analyst in banking,can you please help me to suggest if self-study or doing a master's is a good option for data science
Thank you for this video. Can you please do a video on using Gemini Advanced for Data Analytics? I curious as to how it would perform compared to Chatgpt 4.
I have ChatGPT 4 and in settings for Beta Features, I only have the option to enable plugins and not the Advanced Data Analyst. What should I do to enable this beta features? Reference @ 18:34
I took the course (which was great btw) and was very excited to create a custom GPT. I uploaded three CSV files to use as knowledge data. I provided the key column for each relationship. There are a Company file, statistical question file and a statistical answer file (with two years of data). The experience was laughable. I instructed ChatGPT to only use the data I provided and it constantly made up responses. It even made up data as it was telling me HOW it was coming up with the FAKE responses. I would ask a question like "How many widgets did Acme Corp sell in 2023?" It would respond like "I see Acme Corp listed in the Company file and it is company 1234 (there was no company with that ID). I see the code for the widget question in the Stats Questions file is WDGT (that didn't exist) and the data in the Answers file linked by the question code. So Acme Corp sold 552 widgets (it made up that number)." I must have tried 25 different ways to tell it what is was doing wrong and it would sound like it "Got it" but it only gave me the correct answer once. When I changed the question, it screwed up in new ways. Has anyone had this type of experience?
have you find a way to solve this problem? Have similar experiences
Thank you for sharing all this knowledge!
Amazing to find this available on UA-cam
Hello Luke, I had some issues generating the machine learning model. I tried and tried but chatgpt said "
Error analyzing
It seems I've encountered limitations that prevent executing machine learning model training, specifically with the Random Forest Regressor, directly in this environment. This limitation is related to the operational constraints of the platform rather than an issue with the code itself.
Although I'm designed to assist with generating and explaining code, including machine learning models, the execution of certain tasks, especially those requiring extensive computational resources or specific library functions like scikit-learn, might exceed the capabilities provided here. For running complex machine learning models like the Random Forest Regressor, I recommend using a local Python environment or a dedicated data science platform. These environments offer the computational resources and library support needed for such tasks, allowing you to train, test, and deploy machine learning models effectively." Thank you for your help.
just got the course and wow! totally worth it. great job with all of the resources. I thought it was just a donation thing, but was surprised by how affordable it is. excited to start!
Thanks for contributing!
Great intro course but is there a way i can get more details into Predictive and Prescriptive Data analytics. Like, go more into details. I will gladly pay for such a course.
Hi Luke. I am completely new in this field. I always loved doing analyses in excel. But I found my self limited. Now I am going through your course of SQL and also went through this course. I was able to set up local LLM using LM Studio (on MacBook Air M2) and get it running in VS Code via Continue extension. My question is, have you tried some locally running LLM? Also I recently found Microsoft LIDA. It would be great if we have your opinion on this tools.
Luke - now I have Team subcription and I can work with chatGPT at work - the course is very usuful:) - thank you
So glad OpenAI finally released the Team subscription; glad to hear you're gettin use!
Bro thank you for sharing such great content. Using the screenshot of powerbi's relationship view to get gpt to generate the script felt like magic.
felt the same way when I learned that trick! Glad you felt the same!
Silly question, I would love to do this kind of analysis with my job (not data analysis/nerd job more of a numbers nerd with a data bent) any sources I can go to find a similar for accounting-finance jobs?
Hi, Luke - ref. Settings: You advised to make sure we allow both Pluggins and ADA under Settings. However, my ChatGPT settings only show Pluggins, and not ADA (I refer to minute 34:47 of your clip). is there a problem with the Settings? What should I do? Thank you!
Thank you Man, Congrats for this Nuggest Of Gold
Hi thanks for the great course! After subscribing for ChatGPT Plus (20$/month), it seems the usage policy is limiting usage after about 20 messages.
Any recommendation how to deal with this limitation? Thanks
I am planning to buy your course ChatGPT for Data Analytics.
Is it okay to become a data analyst without knowing coding?
Can I get a good job and salary?
Can the company accept me to do data analysis with the chat gpt4?
Please let me know.
The value here is just insane
Mon premier commentaire pour une video youtube. Ce cours est complet et grand merci pour avoir dedié autant de temps pour nous. Merci
🙌🙌🙌
Hello Luke. Great video as always. In yr view, how would you like to rate gpt + plus response's accuracy and reliability especially for data analysis and simple ML model result?
Hi Luke thank you for this awesome tutorial. It realy makes me happy!
i have a question. I have followed the instructions, but chatgpt reponds it cannot build a model. In stead is responds a method to build a random forrest model with python etc. Has something changed of am i doing something wrong?
thank you for a response.
Joost (The Netherlands)
How do you get all the analysis produced as a report presentable to stakeholders?
Thank you Luke for this incredibly helpful course but all plugins have been discontinued and even ADA isn't offered anymore although if you ask chaGPT about it, it will give you similar features of its data analysis although not necessarily all of the ones mentioned in your course.
My biggest problem with ChatGPT is the inability to save data which you may be compiling. There should be a option to save a certain about of numerical data to reuse in your next analysis session vs having to reload each time
Great course Luke! I was wondering if whenever I upload a dataset file into a GPT chat, then I close the chat, then I reopen the chat, will the dataset file disappear? When I reopen the chat, and enter a new prompt to display a chart, it instead shows the python code. I would have to reupload the dataset file in order for the prompt to work
Also sometimes whenever I reupload the dataset file (both as a zip and csv file), I get an error message saying that there was an issue extracting the contents from the file. How to resolve the issue?
You say that Harvard suggests an improvement with the use of ChatGPT; is this the same study you mentioned in a previous video, that included the stipulation 'if it is within the scope' of what ChatGPT/the data nerd can do?
I just recall that it suggested that data nerds did worse if it was outside the scope and they used ChatGPT wrong - I'm wondering if there has been some improvement that means this isn't true any more?
i love you man - most valuable content on youtube
🫶
Would love same tutorial on BingChat pro with all Windows Office applications integration now Excel,Word etc.
Love your videos and the presentation
Loved this ... Awesome job Luke
Hey Luke currently there is no beta feature in settings . How can I add plugins?
Advanced Data analysis is not showing up as an option (either on 3.5 or 4.0).
I have the feeling that once I finish learning Python, it won't be useful anymore. This AI things grows quickly.
Great curse. Really impressive! Thanks a lot, one of the best channel of UA-cam.
Hi Luke, I have been experiencing frequent and prolonged errors with ChatGPT’s inability to read Excel, CSV and other file types. Even very small datasets seem to be a problem. Do you know whether this problem also persists in the USA, I'm living in the Netherlands Has anyone else experienced this issue? I think this is a major shortcoming of a service for which you also have to pay monthly
What about data safety ? Doesn't chatgpt process later on that amount of data and feed itself with it ? Nothing is for free.
Hey @LukeBarousse , been watching your channel for quite some time big fan! I am somewhat mid level data analyst, at my job I struggle to problem solve and how to solution when given tasks. I tend to get stuck when using excel. Any tips to help with this?
When I try to execute the model I get this response "there was an issue with executing the model due to system limitations. I recommend the following steps to run this machine learning pipeline locally." I have a local environment to run this in and even a Google Colab account, but I'm sure this would be a show stopper for the non-technical audience.
Thanks a lot for this. Bookmarked now.
Good video! Couldn't find the plug in thou...
Yeah plugins have been changing lately so that's why I mention just to find a similar one
Thank You so much Luke for this video!
Thank you so much for the content Luke... you are amazing. 🛠🎲📈
At minute 50:18, the prompt you use isnt working for me. ChatGPT says that it can't excecute due to limitations. Do you have any idea how I can fix this?
The video provided a comprehensive range of valuable information and proved to be extremely useful. This comment has been written using CHATGPT.
Very helpful video. Thanks
Thank you so much for this. Its really helpful 😊
great course man thank you 🙌
Hey master Luke, great opportunity this again. Can I ask, when you go to the link in the vid there are three vids with you can click on, it goes to the same page where you can pay to support you. Is it 3x 25$ or just one time? Love to support to keep up the great work you do
it's just a one time not 3x
Done !!!
Thanks you for your time
Luke, is your video useful for 3.5 version as well?
For this course, you need the paid version so you can upload files and use other more advanced features
18:34. Why doesn't my "beta features" list include "advanced data analysis"? I only see "plugins". Is it possibly because I don't have extensive use of ChatGPT yet?
I asked ChatGPT that question and it responded that's it's part of the Enterprise Plan
It's no longer has to be enabled, it's auto-included in the most advanced model. Don't worry about selecting it.
Does bing do the same?
I'm constantly having to reupload the data. This makes going through this course a bit of pain when you can't go through the entire course in one sitting. Is this because I'm not using the Enterprise subscription? Or is this how it works regardless of subscription level.
I just asked ChatGPT about this and it's a limitation regardless your tier. But as mentioned in the video ChatGPT seems to retain the progress. Not sure how that makes sense though.
This is pure gold
buddy thank you so much for teaching us so much on UA-cam. But... am I the only one having ONLY problem problem problem?! My ChatGPT (4, of course) only answers: i have a problem, i cannot perform this, i cannot perform that, I apologize, i have a technical problem, the problem is permanent, I am sorry but... That's it. Especially with the dataset you provided (which is way too big even to be opened on my excel...). If i use a smaller dataset "sometimes" i can see some elaboration and ChatGPT at least tryies to help as much as it can (few). Please consider i am copying and pasting your exact prompt. No way to work here. Just 20% of times, the rest is "i have a technical problem, i am sorry...." and "error analyzing".
Frustrating is not enough. Is ChatGPT still working or not?!
I'm trying to connect to the data source (40:00) but the zip file is 60MB, so when I try to attach it to ChatGPT, the file exceeds the limit, even with Pro. It doesn't allow me to send the attachment, with the send button grayed out. Any fixes for this?
Hi, ADA plugin is not available in chatgpt plus now. I can't get the similar responses as you have in this course. Any update?
There is no need to enable the ADA plugin it's included in GPT-4 automatically
2022 is the most up to date info that chat gpt can access.
I'm highly convinced your the highlander 💯💯💯👀😂subscribed
Thanks for the sub!
Excelent course mate!
Got my certificate! Woo hoo.
And one more question there is limit of 50 messages / 3 hour so that's very low limit, so how can you continue working with this even I have the pro version but still it's not worth enough because you cannot use it continuously because you there is a message cap limit.
I only run into to this limit ever so often... it does suck... but I don't find I hit it all the time
You are the best ! 😮
Thanks you for your time
Incredible luke❤
Thanks Luke!!!
No problem, cuz!!
this is GPT 4 the paid version ?
I watched the whole thing, it was great.
14 mins after Upload. Nice
@@kestixmac😂😂😂
Hi pls i can become a data analyst and get jobs knowing how to only use chatgpt to do data analysis
*ChatGPT for Data Analytics: A Comprehensive Course Breakdown*
*1⃣ Intro to ChatGPT (**0:00** - **26:37**)*
* *0:00** Introduction:* This course teaches how to use ChatGPT for data analytics, showcasing its time-saving potential and applications.
* *0:27** Course Overview:* The course is divided into six chapters covering ChatGPT setup, prompting, plugins, data collection, and data analysis.
* *2:22** Options & Setup:*
* *Free vs. Plus:* Free version is not suitable for the course; ChatGPT Plus is required for advanced features and costs $20 per month.
* *Team vs. Enterprise:* Enterprise edition offers secure handling of sensitive data, ideal for businesses, while Team offers reduced features for smaller teams.
* *Setup:* Signing up and upgrading to ChatGPT Plus is demonstrated.
* *6:59** Walkthrough:* ChatGPT's interface is explored, covering the sidebar, chat history, settings, and access to custom-built models (GPTs).
* *9:00** Utilizing ChatGPT's Capabilities:* Basic prompting techniques are demonstrated, emphasizing the importance of clear context and task definition for accurate results.
* *11:18** Personal Context Statements:* Creating personal context statements to guide ChatGPT's responses is encouraged.
* *12:12** Updating ChatGPT's Knowledge:* ChatGPT has a knowledge cut-off date (currently April 2023) and uses internet browsing for up-to-date information.
* *14:03** Mastering Prompting Techniques:* Improving prompting with context and task considerations for better results.
* *16:33** Setting Up Custom Instructions:* Setting up custom instructions for personalized and efficient use.
* *20:43** ChatGPT's Image Analysis:* ChatGPT can analyze images, enabling interpretation of graphs and visualizations.
*2⃣ Intro to Advanced Data Analysis (**26:38** - **1:01:57**)*
* *26:38** Chapter Intro:* This chapter focuses on using ChatGPT's Advanced Data Analysis plugin for data exploration, statistics, and machine learning predictions.
* *28:28** ADA Timeout Issues:* A temporary bug where Advanced Data Analysis sessions might time out, requiring re-uploading of files.
* *30:00** ADA Intro:* Comparison between ChatGPT with and without Advanced Data Analysis, highlighting its significance for data tasks.
* *36:02** Advanced Data Analysis Execution:* ChatGPT's Advanced Data Analysis feature executes Python code directly in the chat interface, allowing users to verify calculations.
* *36:57** Versatility of Advanced Data Analysis:* The feature can handle various tasks, including data processing, statistical analysis, predictive modeling, and custom queries.
* *38:03** File Type Flexibility:* ChatGPT accepts various file types for data analysis, including CSV, Excel, Json, and more.
* *41:16** Descriptive & Exploratory Data Analysis:* ChatGPT performs descriptive statistics and exploratory data analysis (EDA), providing insights through visualizations.
* *46:06** Importance of Data Cleanup:* Data cleanup is crucial for accurate analysis, including removing spaces or renaming columns.
* *48:08** Complex Data Visualization:* Visualizations, such as analyzing salary data in relation to job platforms, titles, and locations, offer deeper insights.
* *52:29** Machine Learning Predictions:* ChatGPT builds machine learning models, like Random Forest, to predict data, such as yearly salaries.
* *55:36** Understanding Model Error Metrics:* Root Mean Square Error (RMSE) evaluates the model's accuracy, indicating the average deviation from actual salaries.
* *56:30** Testing the Predictive Model:* Testing the model with real-world scenarios demonstrates its practical application.
* *58:06** Model Performance Variability:* Predictive accuracy varies across different roles, highlighting the importance of a diverse dataset.
* *59:42** Internet Access Limitation:* Advanced Data Analysis cannot directly connect to online data sources, limiting its ability to analyze internet data.
* *1:00:24** File Size Limitation:* There's a 512MB file size limit for uploads to ChatGPT.
* *1:01:58** Chapter Outro:* The chapter summarizes the importance of using Advanced Data Analysis for ad-hoc analysis and highlights the potential for future advancements.
*3⃣ Basic Analysis (**1:03:27** - **2:09:04**)*
* *1:03:27** Chapter Intro:* This chapter dives into basic visualizations and common statistics for those new to data analytics.
* *1:07:11** Core Visualization:* Six common visualizations are explored: bar charts, line charts, pie charts, and scatter plots, with examples and use cases.
* *1:16:32** Statistical Visualizations:* Histograms and box plots are examined for visualizing distributions and comparing data.
* *1:27:16** Visualization Best Practices:* Recommendations for clutter-free visuals, focused attention, and effective communication with visualizations.
* *1:38:02** Basic Statistics:* This section covers descriptive statistics for numerical and categorical data.
* *1:50:34** Four Types of Data Analytics:* The four core types of data analytics are introduced: descriptive, diagnostic, predictive, and prescriptive.
* *1:54:43** Descriptive Analysis:* Descriptive analysis focuses on understanding past data, using descriptive statistics and EDA.
* *1:59:06** Diagnostic Analysis:* Diagnostic analysis explores the "why" behind observed trends, using drill-downs and further exploration of data.
* *2:04:57** Predictive Analysis:* Predictive analysis uses past data to forecast future trends, often employing machine learning models.
* *2:09:05** Prescriptive Analysis:* Prescriptive analysis provides recommendations for action based on predictions and insights.
*4⃣ Advanced ChatGPT (**2:12:56** - **2:47:32**)*
* *2:12:56** Chapter Intro:* This chapter focuses on mitigating hallucinations, mastering prompting techniques, and understanding GPTs (customized ChatGPT models).
* *2:18:11** Hallucinations:* Hallucinations, where ChatGPT provides incorrect information, are explored with real-world examples and explanations.
* *2:25:48** Prompting Best Practices:* A six-part prompt formula is introduced for improving ChatGPT's responses, including task, context, exemplar, persona, format, and tone.
* *2:33:14** Custom Instructions:* Custom instructions are demonstrated as a method for automating context, format, and tone preferences in ChatGPT.
* *2:39:01** GPTs:* GPTs, custom-built ChatGPT models, are explored with examples and instructions on building GPTs for specific tasks.
* *2:47:13** Creating a Personalized GPT:* The importance of refining and improving custom GPTs for optimal results is emphasized.
*5⃣ Intro to Plugins (**2:47:33** - **3:08:09**)*
* *2:47:33** Chapter Intro:* This chapter introduces ChatGPT plugins for enhancing functionality and explores the benefits of using plugins for time-saving and automation.
* *2:53:16** Browse with Bing:* Browsing the internet with ChatGPT is explored, highlighting its usefulness for retrieving up-to-date information.
* *2:58:27** Time-Saver Plugins:* Various plugins are showcased for summarizing PDFs, web pages, articles, videos, and general knowledge.
* *3:03:27** Wolfram Plugin:* The Wolfram plugin is explored for accessing a curated knowledge base of data, especially valuable for scientific and technical information.
* *3:08:17** DALL-E 3 Plugin for Image Generation:* The DALL-E 3 plugin is introduced for generating images from text prompts, providing creative and visually appealing outputs.
*6⃣ Data Collection (**3:13:18** - **3:33:48**)*
* *3:13:18** Chapter Intro:* This chapter focuses on data collection methods, including finding public datasets, web scraping, and utilizing APIs.
* *3:16:51** Public Data Sets:* Resources for finding public datasets are discussed, including Kaggle, GitHub, Reddit, and Google Dataset Search.
* *3:20:58** Web Scraping Intro:* Web scraping is introduced as a method for extracting information from websites, emphasizing legal and ethical considerations.
* *3:29:22** Using ChatGPT for Data Extraction:* An example of legally extracting data from Glassdoor job postings is demonstrated using ChatGPT's Advanced Data Analysis plugin.
* *3:30:27** Advanced Concepts in Web Scraping:* A deeper dive into the legality of web scraping is provided, highlighting a landmark case involving LinkedIn and data scraping.
* *3:32:19** Checking Website Legality for Scraping:* Methods for verifying whether a website allows scraping are discussed, including checking robots.txt files and terms of service.
* *3:33:49** Course Wrap-up:* The course concludes with a reminder to complete the end-of-course survey to receive a certificate and further promotes the use of ChatGPT for data analysis.
I used gemini-1.5-flash-latest to summarize the transcript.
Cost (if I didn't use the free tier): $0.0072
Input tokens: 87318
Output tokens: 2043
Luke you are the best
Thank you!
my chat gpt cant analyse same csv file says error analysing tried different ways still can't do it anyone having same issue and resolved? using gpt4
Bro you are a goat i needed that
😉
Thanks for sharing 🙏
Brilliant!
I paid for your full course, what is the difference from this?
Thank you for your sacrifice ❤
Thank you for making this course possible and accessible for everyone. I salute you.
You could ask ChatGPT that question then ;-)
Lmfao
Hey @jesus629, this is the same content from my course back in November, but packaged up into a single UA-cam video. The full course that you have has everything broken down into different segments for the chapters, making it easier to navigate and track.
Nonetheless, you should have received an email a month ago asking if you'd like a refund for the course due to the deprecation of the "Noteable" plug-in. Hit me up via email if you want to go that route
Thank you!!!
What that dinging sound? Sounds familiar....🤐
let's gooooooooo!!!!! Gracias
🙌