Are you interested in becoming an AI developer? AI developers are one of the hottest jobs in IT markets with an average salary of 21 lakhs per annum. In this article, we’ll guide you through seven of the best free AI courses available online to help you become an AI developer.
Starting from the fundamentals and advancing to more complex topics.
Course 1. Mathematics Fundamentals
Before knowing about AI, machine learning, and data science, it’s crucial to establish a strong foundation in mathematics.
You don’t need to be a math genius, but you should grasp essential concepts. Focus on understanding:
- Linear algebra
- Matrices and determinants
- Matrix multiplication
- Eigenvalues and eigenvectors
- Different types of probabilities
- Statistical data representation
To get started, John’s YouTube playlist on linear algebra and probability will provide you with a comprehensive introduction to these essential mathematical concepts. For those seeking personalized assistance, there are excellent options for math tutoring in Henderson to further enhance your understanding and skills.
Course 2. Learn a Programming Language
To communicate with computers and develop AI and machine learning models, you need to learn a programming language.
Python is the go-to language for most AI developers due to its user-friendliness. It’s an excellent choice for beginners, and you can quickly understand the code.
You can begin with the basics, such as:
- Data types
- Conditionals
- Loops
- Functions
- Objects and classes
Check out the four-hour-long video on the freeCodeCamp YouTube channel to learn Python.
Once you have a basic understanding, you can apply your knowledge by solving real-world problems.
Course 3. Master Python Libraries
Python libraries play a significant role in data science and AI development.
Three essential libraries you should learn are:
- NumPy: Helps organize and manipulate data into multi-dimensional arrays.
- Pandas: Allows querying and analyzing data from various sources.
- Matplotlib: Used for data visualization.
To master these libraries, watch the video on the freeCodeCamp channel.
This video covers the basics and provides practical examples to help you apply what you’ve learned.
Course 4. Introduction to Machine Learning
Now that you have a solid grasp of mathematics, programming, and Python libraries. It’s time to explore machine learning concepts.
Tech with Tim’s YouTube channel offers a comprehensive video covering:
- Supervised learning
- Unsupervised learning
- Reinforcement learning
- Building machine learning models
Throughout the course, you’ll work on various projects, including linear regression, classification, K-nearest neighbors, support vector machines, and unsupervised learning techniques.
Course 5. TensorFlow Basics
TensorFlow is a popular framework for building machine learning and AI models.
Google offers a concise course on TensorFlow, where you’ll learn to create deep neural networks efficiently.
Topics covered include:
- Keras
- Building deep neural networks
- Validating sets, training sets, and test sets
- Weight and bias optimization
- Regression and classification
By completing this course, you’ll gain the skills needed to work with TensorFlow effectively.
Course 6. Natural Language Processing (NLP)
Natural Language Processing (NLP) is a vital aspect of AI development, particularly for tasks like chatbots and language understanding.
Stanford University offers a free course, CS224N, available on YouTube. This course explores:
- Text parsing and understanding
- Transformer models
- Large language models
- Practical applications of NLP
The course, taught by experienced professors from Stanford, offers a deep understanding of NLP.
Course 7. ChatGPT and Generative AI
Deep Learning AI offers a course on ChatGPT prompt engineering for developers, taught by Andrew Ng. This course helps you understand the principles of ChatGPT and generative AI, making it easy to create applications based on generative AI models.
In addition, Deep Learning AI offers three short courses covering different aspects of generative AI, including GPT-3 API usage.
Bonus: Problem-Solving and Practice
To grow as an AI developer, you should continuously practice and solve real-world problems. Platforms like Kaggle provide various AI and machine learning challenges to put your skills to the test.
Now that you’ve explored these free AI courses, you’re well on your way to becoming a proficient AI developer. The artificial Intelligence field requires continuous learning and practice. You’ll be prepared to secure a high-paying job in the exciting world of AI development.
Conclusion:
That concludes our guide on the seven free AI courses to help you become an AI developer in 2023. If you have any questions or need further assistance, feel free to reach out in the comments section. Don’t forget to check out our latest AI Tutorials.
