Starting from Zero: An Easy Roadmap to AI and ML

Module 0 - Before You Start

Before you begin, it is best to build your foundations and have the set-up ready. This would help you get your system working for Python on a compiler software. Mathematics is a foundation for everything in the world for Artificial Intelligence. Have a core in applied mathematical concepts like linear algebra, matrics and more can help you theoretically understand how machines work.

Module 1 - The Math Behind It All

The domain of AI/ML is a vast deep ocean and it's time for you to build a boat and rafters for a smooth sail. These foundational courses in Computer Science and Python Programming will get you going strong!

Module 2 - Building Your Foundation

The domain of AI/ML is a vast deep ocean and it's time for you to build a boat and rafters for a smooth sail. These foundational courses in Computer Science and Python Programming will get you going strong!

Module 3 - Data Science

Data is the new oil! Before jumping into making advanced AI, let's learn about the data that drives it. We'll cover basics of statistics and Data Science using Python in this module.

Module 4 - Machine Learning

Time to use that data to train a machine on how to learn them. Machine learning is the science of computer algorithms that help machines learn and improve from data analysis without explicit programming. THAT'S SO COOL!

\❗ The ML Specialization by Andrew NG is a highly specialized and industry level course by one of the most promient AI scientist - Andrew NG. It is an expert level course and is highly recommened to do one you get a good grasp of the foundational knowledge.*

Module 5 - Computer Vision

Giving the power of vision to our intelligent computers! Computer Vision trains computers to interpret and understand the visual world, just the way we see it (or in an more advanced way ;))

Module 6 - Deep Learning Neural Network

Time to harness the power of our human brain to develop something that resembles the powers of a human brain. Neural Networks help you understand how information is processed from raw data like the human brain to mimic desired outputs.

Module 7 - Generative AI

The big buzz word everywhere! Create text, images, audios, videos, and more all thanks to Generative Adversarial Networks!

Sub-Module 7A - Retrieval Augmented Generation (RAG)

Retrieval-augmented generation (RAG) is a natural language processing (NLP) technique that combines the capabilities of traditional information retrieval systems with the strengths of generative large language models (LLMs)

Module 8 - Natural Language Processing

English, Spanish, French, Hindi, Tamil, Russian, Python, Java, C++ and wait what? Let's learn how can we help computers understand our human language better (the natural language)

Module 9 - Reinforcement Learning

Walk, fall, get up, learn, repeat. Just like how humans learn through experiences on what to do and what not to do, AI is no different!

Module 10 - Agentic AI

Don't just provide the solutions, start acting on it. Agentic AI workflows integrate AI and operations to fuel the next wave automation like never before.

Bonus Module - Advanced Learning Pathway Courses

Additional bonus courses and problem solving exercises.

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Written by

Upadrasta Harsha
Upadrasta Harsha

Hi I am Harsha vardhan upadrasta, a 21 year old Web developer, ui/ux designer, and a bug hunter living in Draksharama, India. I am a Computer Science Engineer, currently working with awesome folks at _VOIS.