7 FREE AI Courses To Become an AI Developer in 2023

 

Seven Free Online Courses to Become an AI Developer

AI development is one of the hottest jobs today, with an average salary of 21 lakhs per annum. If you want to take advantage of this trend and become an AI developer, here are the seven best free courses you can take online to learn from the basics to the advanced level:

• Mathematics
• Programming Language (Python)
• Python Libraries (NumPy, Pandas, Matplotlib)
• Machine Learning
• TensorFlow Framework
• Natural Language Processing
• Deep Learning

Mathematics

Before diving into AI, it is essential to understand the underlying mathematics. You need to focus on concepts like linear algebra, matrices, determinants, matrix multiplication, eigenvalues, eigenvectors, probabilities, and statistics. John's YouTube playlist is an excellent resource for learning these concepts.

Programming Language (Python)

Python is the most widely used language for creating ML models. It is a user-friendly language that you can start using as a complete beginner. The freeCodeCamp YouTube channel offers a great four-hour-long video that covers everything from basic data types to objects and classes.

Python Libraries (NumPy, Pandas, Matplotlib)

NumPy, Pandas, and Matplotlib are three essential libraries for data science. NumPy helps organize data into a multidimensional array, Pandas queries data from a database, and Matplotlib visualizes data. Akash's video on the freeCodeCamp YouTube channel is an excellent resource for learning about these libraries.

Machine Learning

Machine learning is a very exciting field that you will start learning about in this course. Tech with Tim's YouTube channel offers an amazing video that covers everything from supervised learning to reinforcement learning. You will learn about linear regression, classification, k-nearest neighbors, support vector machines, and unsupervised learning methods. Tim also teaches how to build a simple Flappy Bird game in this course.

TensorFlow Framework

TensorFlow is a framework that helps create amazing ML and AI models. Google offers a short course that teaches the basics of this framework. You will learn about Keras, deep neural networks, validating sets, training sets, test sets, optimizing weights and biases, regression, and classification.

Natural Language Processing

Stanford CS224N YouTube playlist is a course that teaches you how to parse text and understand it to create the next prediction for what the next text would be. You will learn about transformers, BOLT, large language models, and how chat GPT and other programs like BARD operate.

Deep Learning

Deep learning is the next step after you have learned about natural language processing. Andrew Ng's Deep Learning Specialization course on Coursera is an excellent resource for learning about deep learning.

Newton School of Technology offers a futuristic curriculum and a bachelor's degree in computer science and AI. They provide top faculties from MIT, Duke, and IITs, personal mentoring from CEOs and CXOs of 500 plus top companies like Google, Amazon, and more, a six-month long paid internship experience, study trips, and tech conferences in global tech hubs like Silicon Valley, Singapore, Israel, and many more. The average package is 12 lakh per annum. All students get a MacBook with M2 chip and can also get scholarships up to 100% through NSAT.

Register for Newton's Scholastic and Aptitude Test (NSAT) with the link in the description as soon as possible. The exam date is 28 June and 10th July. The scholarship seats are limited, so do not miss out on this opportunity.

Learning Generative AI: Courses to Take

If you're interested in learning about chart GPT, there are several courses available to help you get started. One great option is the "Chart GPT Prompt Engineering for Developers" course by Deep Learning dot AI, taught by Andrew Ng. This course will teach you how to use chart GPT for prompt engineering and how to use the chart GPT API. You'll also learn about generative AI and how to create applications based on it.

In addition to this course, Deep Learning dot AI also offers three shorter courses that provide a basic understanding of chart GPT and its applications. These courses cover both prompt engineering and the chart GPT API.

Google also offers a comprehensive learning path that includes 10 different courses on generative AI. This path covers the basics of generative AI, including large language models, world and transformers, and image generation. You'll also learn about diffusion models and how to create a simple image captioning model. Finally, you'll have the opportunity to interact with the generative AI studio from Google.

By completing this learning path, you'll be well-prepared for a career as an AI developer. Of course, you'll need to continue practicing and solving problems on platforms like Kaggle, and exploring other tools in the generative AI space, such as auto GPT.

Check out the links in the description to learn more about these courses. And don't forget to tag me on social media (@ishansharma90) if you have any questions!