Are you confused about where to start learning Artificial Intelligence? 🤔
In this video, I’ll give you a complete practical AI roadmap — step by step, from Python foundations all the way to Machine Learning, Deep Learning, Generative AI, and Agentic AI frameworks.
00:00 Intro
01:13 Role of AI Engineer
01:58 Python Foundations
02:36 API
04:41 Databases
07:00 Machine Learning
10:15 Deep Learning
13:19 Generative AI
17:10 What Next?
Watch – Building a Resume Screening Application:
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Watch – Complete RAG Playlist:
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Deep Learning Datasets:
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MNIST Dataset:
https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz
Dogs Vs Cats Data:
https://www.kaggle.com/c/dogs-vs-cats/data
Sentiment Analysis on Tweets:
https://www.kaggle.com/datasets/jp797498e/twitter-entity-sentiment-analysis
Machine Learning datasets:
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Student Score Predictor Dataset:https://www.kaggle.com/datasets/spscientist/students-performance-in-exams
SMS Spam Collection Dataset:
https://www.kaggle.com/datasets/uciml/sms-spam-collection-dataset
Customer Segmentation Dataset:
https://www.kaggle.com/datasets/vjchoudhary7/customer-segmentation-tutorial-in-python
This roadmap is designed to keep theory minimal and focus on projects, so you learn AI by building real-world applications.
👉 What You’ll Learn:
Python Foundations (lists, loops, functions, dictionaries)
API Development Basics with FastAPI
Databases (SQL fundamentals & mini projects)
Machine Learning (Regression, Classification, Clustering with Kaggle datasets)
Deep Learning (Digit Recognition, CNN Image Classifier, Text Classification)
Generative AI (Summarizers, PDF Q&A Bots, YouTube Summarizer)
Agentic AI (Travel Planner, API Calling Agents, Bonus RAG Project)
By following this roadmap consistently, you’ll gain the skills needed to grow as a real AI Engineer.
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