TGViewer
Machine Learning & Artificial Intelligence | Data Science Free Courses Machine Learning & Artificial Intelligence | Data Science Free Courses @datasciencefree Β· 68.6K subscribers
Post #1789 2.37K
Complete Roadmap to learn Machine Learning and Artificial Intelligence
πŸ‘‡πŸ‘‡

Week 1-2: Introduction to Machine Learning
- Learn the basics of Python programming language (if you are not already familiar with it)
- Understand the fundamentals of Machine Learning concepts such as supervised learning, unsupervised learning, and reinforcement learning
- Study linear algebra and calculus basics
- Complete online courses like Andrew Ng's Machine Learning course on Coursera

Week 3-4: Deep Learning Fundamentals
- Dive into neural networks and deep learning
- Learn about different types of neural networks like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs)
- Implement deep learning models using frameworks like TensorFlow or PyTorch
- Complete online courses like Deep Learning Specialization on Coursera

Week 5-6: Natural Language Processing (NLP) and Computer Vision
- Explore NLP techniques such as tokenization, word embeddings, and sentiment analysis
- Dive into computer vision concepts like image classification, object detection, and image segmentation
- Work on projects involving NLP and Computer Vision applications

Week 7-8: Reinforcement Learning and AI Applications
- Learn about Reinforcement Learning algorithms like Q-learning and Deep Q Networks
- Explore AI applications in fields like healthcare, finance, and autonomous vehicles
- Work on a final project that combines different aspects of Machine Learning and AI

Additional Tips:
- Practice coding regularly to strengthen your programming skills
- Join online communities like Kaggle or GitHub to collaborate with other learners
- Read research papers and articles to stay updated on the latest advancements in the field

Pro Tip: Roadmap won't help unless you start working on it consistently. Start working on projects as early as possible.

2 months are good as a starting point to get grasp the basics of ML & AI but mastering it is very difficult as AI keeps evolving every day.

Best Resources to learn ML & AI πŸ‘‡

Learn Python for Free

Prompt Engineering Course

Prompt Engineering Guide

Data Science Course

Google Cloud Generative AI Path

Unlock the power of Generative AI Models

Machine Learning with Python Free Course

Machine Learning Free Book

Deep Learning Nanodegree Program with Real-world Projects

AI, Machine Learning and Deep Learning

Join @free4unow_backup for more free courses

ENJOY LEARNINGπŸ‘πŸ‘
  • ❀ 10
More from @datasciencefree
  1. Sep 27, 2026Machine Learning Roadmap | |-- Fundamentals | |-- Mathematics | | |-- Linear Algebra | | |…
  2. Sep 24, 2026πŸš€ 𝐁𝐞𝐜𝐨𝐦𝐞 𝐚𝐧 π€πˆ π„π§π π’π§πžπžπ« 𝐒𝐧 πŸπŸŽπŸπŸ” 🎯 Choose Your Learning Track: πŸ’»β€¦
  3. Sep 23, 2026Machine Learning Roadmap
  4. Sep 23, 2026SQL & Python Cheatsheet for Beginners ❀️
  5. Sep 22, 2026#Ad #AI_Models πŸ”₯ GigaChat 3.5 Reasoning [Open-Source] ℹ️ Overview: New LLM that thinks be…
  6. Sep 22, 2026βœ… Programming Languages, Libraries & Tools Every Tech Field Uses πŸ‘¨β€πŸ’»πŸš€ 🧠 DATA SCIENCE &…
Threads Profile ViewerView any public Threads profile without an account.Open ThreadLook β†’Writing with AI? Make it sound human.Metric37 rewrites AI drafts so they read naturally. Free AI detector, 1,500 words free.Try Metric37 β†’