AI/ML Roadmap 2024: Step-by-Step Guide to Mastering AI and Machine Learning from Beginner to Pro [Video]

Video Design Structure:

1. Introduction
• Brief personal introduction and a hook about why AI/ML is crucial for the future.
• Mention who this video is for (beginners, students, professionals, etc.).
2. Overview of AI/ML
• Explanation of AI and Machine Learning concepts.
• Discuss the growth and applications of AI in various industries.
3. Prerequisites
• Recommended programming languages (Python, R).
• Mathematical foundations: Linear algebra, probability, calculus, statistics.
• Basic understanding of data structures and algorithms.
4. Beginner Stage
• Start with Python for data science (NumPy, Pandas).
• Introduce machine learning basics (Supervised and Unsupervised Learning).
• Explore simple models (Logistic Regression, Decision Trees) using Scikit-learn.
5. Intermediate Stage
• Explore advanced algorithms (SVM, Random Forest, K-Means).
• Introduction to Neural Networks and Deep Learning (TensorFlow/PyTorch).
• Focus on real-world projects (image classification, sentiment analysis).
6. Advanced Stage
• Advanced topics such as Reinforcement learning, NLP, and Computer Vision.
• Building AI/ML models using deep learning techniques.
• Deployment of models on platforms like Google Cloud, AWS.
7. Resources and Roadmap Tools
• Provide free and paid learning resources (Coursera, edX, GitHub repositories).
• Discuss ways to stay updated with the field (research papers, conferences).
8. Conclusion and Call to Action
• Summarize the roadmap.
• Encourage viewers to subscribe, like, and leave comments.
• Mention upcoming related content on AI/ML.

In this video, I am sharing educational content about coding and algorithms. This material uses Siri’s voice to enhance your understanding.

This video is created purely for educational purposes, aiming to share knowledge. I have used this voice in compliance with Apple’s terms of use.

Welcome to this video, and I hope you find it helpful!