Are you intrigued by the captivating world of Artificial Intelligence (AI) development?
With an average annual salary of $129,846 USD in the US, AI development is one of the most sought-after careers today.
To embark on this exciting journey, you can take advantage of several free courses available online.
Table of Contents
In this guide, we will outline the seven best courses that will equip you with the knowledge and skills to become an AI developer, from mastering the fundamentals to diving into advanced concepts.
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List of Courses to Become an AI Developer
1. Embrace the Power of Mathematics
Before delving into AI, machine learning, or data science, it’s crucial to grasp the foundational mathematics.
Fear not, as you won’t be solving complex equations; computers will handle that part.
Your focus should be on understanding the concepts of linear algebra, matrices, determinants, matrix multiplication, eigenvalues, eigenvectors, various probability types, and data presentation through statistics.
These concepts are essential prerequisites for your journey into machine learning and artificial intelligence.
One excellent resource to build your mathematical foundation is Jon’s YouTube playlist, where he expertly explains linear algebra and probability concepts.
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2. Master a Programming Language
To communicate effectively with computers for AI and machine learning, you need to learn a programming language.
Python is the most widely used language in this field due to its user-friendliness and versatility. Even if you’re a beginner, Python allows you to understand the code and its workings.
Dive into Python with a comprehensive four-hour video course available on the FreeCodeCamp YouTube channel. This course covers data types, conditionals, loops, functions, objects, and classes.
Once you have a basic understanding of Python, you can apply your knowledge to real-world problems and gain valuable experience.
3. Harness the Power of Python Libraries
Next, you should acquaint yourself with essential Python libraries such as NumPy, Pandas, and Matplotlib. These libraries are instrumental in data science tasks. NumPy helps organize disorganized data into multidimensional arrays (matrices). Pandas enable data querying from databases, while Matplotlib facilitates data visualization.
For a comprehensive introduction to these libraries, check out Akash’s tutorial on the FreeCodeCamp channel. This resource covers everything from the basics to problem-solving, providing hands-on experience.
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4. Explore Machine Learning Fundamentals
Machine learning is an exciting field where you’ll learn about supervised and unsupervised learning, reinforcement learning, and build various machine learning models.
Dive into machine learning with the Tech with Tim YouTube channel, which offers comprehensive tutorials.
You’ll explore linear regression, classification, K-nearest neighbors (KNN), support vector machines, and more.
Tim’s practical approach involves building real projects, which enhances your understanding and problem-solving skills.
5. TensorFlow Essentials
TensorFlow, a robust framework, is indispensable for creating AI and machine learning models.
This framework allows you to build deep neural networks with minimal code.
Google offers a short course on the TensorFlow website, taught by experienced instructors.
You’ll learn about Keras, optimization, regression, classification, and how to build models using TensorFlow.
6. Dive into Natural Language Processing (NLP)
NLP is a fascinating field within AI, focusing on text analysis and understanding.
Explore Stanford’s CS224N course, available for free on YouTube.
You’ll learn about Transformers and large language models, and gain a deeper understanding of how models like GPT-3 operate.
This knowledge is essential for working with generative AI.
7. Master GPT Models
Finally, learn about generative AI, specifically GPT models.
Deep Learning AI offers a course by Andrew Ng on GPT prompt engineering for developers.
You’ll explore GPT’s capabilities, prompt engineering, and application development.
Additionally, explore Google's extensive 10-course learning path on generative AI to become proficient in this exciting field.
My Opinion
With these seven free courses, you’ll acquire the knowledge and skills necessary to become an AI developer.
Remember, continuous learning and practice are key in the rapidly evolving field of artificial intelligence.
Stay curious, explore real-world problems on platforms like Kaggle, and embrace the possibilities of generative AI. The journey to becoming an AI developer is both rewarding and full of opportunities.