A Comprehensive Guide to Learning AI

A Comprehensive Guide to AI Education Resources 

Author: Tom Campbell

30 September, 2024

So, you want to learn about AI, I get it, AI has been the buzzword everywhere for the past year and a half—it’s in the news, in your feeds, and in your employee break room. But with all the chatter, it can be hard to know where to start learning about it.  In this blog, I will list out where you can go to learn the basics about AI, and then I will list out where you can learn more advanced AI. Most importantly, I will list where you can find data to help you in your AI journey. This is not an all-inclusive list of resources, but it will help you on your way to learning AI today. 

Learning AI for Executives and Non-Tech People

If you’re a business executive or someone who isn’t from a technical background, diving into AI can seem daunting. However, there are more than enough resources designed specifically for you. These resources will help you grasp the concepts without getting lost in technical jargon. 

YouTube

https://www.youtube.com/watch?v=K-7WPpSfCQo 

YouTube is loaded with all kinds of videos, but it can be tough to find what you are looking for. The link above is for a video that goes over some examples of AI in action. Try searching for AI Strategy or AI in Action, you should find many videos that will help understand how AI is transforming the business landscape.  

Medium

https://medium.com/swlh/ai-for-beginners-a-high-school-students-explanation-4014c65675c 

Medium has many articles that are perfect for non-technical readers who want to stay current with AI trends and concepts. You can find a variety of topics, including the impact of AI on society or even ethical considerations of AI. The link above provides a nice overview of the AI basics. 

Databricks Blog: Generative AI Insights

https://www.databricks.com/blog/category/generative-ai 

The Databricks blog regularly publishes articles on Generative AI and machine learning. These articles provide insights into the latest trends and practical use cases on the Databricks platform. It’s an excellent resource for both beginners and advanced users looking to deepen their knowledge. 

Xorbix Insights

https://xorbix.com/insights/ 

Yeah, you’re here reading this blog, but we have many other blogs and case studies that cover AI and ML. Visit our insight page and select what you would like to learn more about. 

MIT Professional Education: AI and Machine Learning

https://mit-online.getsmarter.com/presentations/lp/mit-artificial-intelligence-online-short-course/ 

MIT offers paid short, intensive courses covering AI and machine learning, aimed at working professionals. This program Artificial Intelligence: Implications for Business Strategy is about Generative AI platforms that are revolutionizing the way we do business. 

Berkeley Exec Ed: Artificial Intelligence: Business Strategies and Applications

https://em-executive.berkeley.edu/artificial-intelligence-business-strategies 

This short, paid program will introduce you to the basic applications of AI for businesses. Participants will learn about generative AI and learn about automation, machine learning, and robotics. 

Learning AI for Programmers and Technical Individuals

For those with a programming background, there are plenty of in-depth resources to get hands-on experience in AI. These platforms provide tutorials, courses, and community support for building and deploying AI models. A few of these are paid classes. 

Udacity

https://www.udacity.com/course/ai-programming-with-python–nd089 

“AI Programming with Python” is designed for developers, providing practical skills to implement AI models using Python and its libraries. The course includes access to experienced mentors and hands-on projects. 

GitHub Repositories

https://github.com/ 

GitHub hosts numerous open-source AI projects, like TensorFlow and PyTorch. It provides extensive documentation, code examples, and community support for AI practitioners. Developers can contribute to projects, learn from others’ code, and collaborate globally. 

Kaggle

https://www.kaggle.com/ 

Kaggle is well-known for its datasets, tutorials, and AI competitions. It’s an excellent platform for learning and applying machine learning and AI techniques. The platform allows users to engage in competitions that simulate real-world AI challenges. 

OpenAI

https://www.openai.com/research 

OpenAI offers research papers, tutorials, and access to tools like GPT, focusing on the latest advancements in Generative AI and deep learning. Their open research platform helps developers understand and implement AI technologies. 

NVIDIA Deep Learning Institute

https://www.nvidia.com/en-us/training/ 

Provides courses on AI and deep learning, designed to help developers leverage NVIDIA’s GPU-accelerated platforms for building AI solutions. The courses cover essential topics such as model optimization and deployment strategies. 

Carnegie Mellon University: AI Engineering Graduate Certificate

https://www.cmu.edu/online/aimlmeche/index.html 

Carnegie Mellon’s paid program focuses on the practical application of AI in engineering. It covers AI algorithms, robotics, and ethical AI, and is aimed at working professionals who can complete it within 9-12 months. 

Microsoft

https://learn.microsoft.com/en-us/ai/?tabs=developer 

The Microsoft AI learning hub has a lot of content to help you get skilled up and ready to use AI. You can start with the basics and build your skills at your pace. They have materials for all types of people from developers to data scientists, to business users. 

Databricks Academy: Generative AI Courses

https://www.databricks.com/learn/training/home 

Databricks Academy offers a range of courses tailored for data scientists, engineers, and analysts who want to learn how to build AI and ML models on Databricks. The courses cover topics such as machine learning, deep learning, and Generative AI using Databricks’ Lakehouse Platform. The courses are interactive, providing hands-on experience with notebooks, datasets, and guided labs. 

O’Reilly Media

https://www.oreilly.com/ 

O’Reilly is a publisher of in-depth and knowledgeable computer science and software engineering books. Each book often focuses on a niche component of software development or AI concepts. Recently, O’Reilly has published many books on AI and LLM concepts ranging from MLOps, Prompt Engineering, all the way to detailed implementations of Generative Adversarial Networks. Individual books can be purchased from Amazon and retailers. O’Reilly also offers nearly their entire collection on their educational platform for a subscription fee. (Many local libraries have the subscription included with a library card). 

Where to Find Data for AI Projects

Finding the right data is crucial for any AI project. Here are some excellent places where you can find datasets to experiment with. 

Kaggle Datasets

https://www.kaggle.com/datasets 

Kaggle is one of the most popular platforms for data science competitions, but it also hosts a vast repository of datasets covering various domains like healthcare, finance, and more. You can easily download datasets and get started with your AI experiments. 

UCI Machine Learning Repository

https://archive.ics.uci.edu/ml/index.php 

The UCI Machine Learning Repository is a classic source for datasets. It’s been used in countless research papers and offers a wide variety of datasets for machine learning problems. 

Google Dataset Search

https://datasetsearch.research.google.com/ 

Google Dataset Search is like Google for datasets. You can search for any type of dataset you need, and it will pull results from across the web, including government datasets, academic sources, and more. 

Data.gov

https://www.data.gov/ 

Data.gov is a platform where the U.S. government publishes open data. It provides datasets from various government sectors that can be used for a wide range of AI projects. 

AWS Public Datasets

https://registry.opendata.aws/ 

Amazon Web Services (AWS) offers a collection of publicly available datasets that you can use in your AI projects. These datasets are stored in the cloud, making it easier to integrate them directly into your cloud-based AI workflows. 

Conclusion

Whether you’re an executive looking to understand AI’s impact on business or a programmer wanting to get hands-on with machine learning algorithms, there are resources available for every learning style. Start with the basics, get comfortable with the concepts, and then dive into more advanced courses and datasets as you progress on your AI journey. The world of AI is vast, but with the right resources, it becomes much more approachable. 

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