Learn basic math: algebra, probability, statistics, linear algebra, calculus
Learn Python programming
Practice Python libraries: NumPy, pandas, Matplotlib
Learn data structures and algorithms
Study machine learning fundamentals
Learn supervised, unsupervised, and reinforcement learning
Understand model training, validation, and testing
Learn feature engineering and data preprocessing
Study common algorithms: linear regression, logistic regression, decision trees, random forests, SVM, k-means
Learn deep learning fundamentals
Study neural networks, backpropagation, and optimization
Practice with TensorFlow or PyTorch
Learn how to work with datasets
Build small projects with real data
Use Kaggle for practice and competitions
Learn model evaluation metrics
Study overfitting, underfitting, and regularization
Learn basics of NLP, computer vision, and generative AI
Read research papers and technical blogs
Follow AI courses and tutorials
Join AI communities and forums
Keep building projects and improving them
Learn deployment basics: APIs, cloud, and containers
Create a portfolio of AI projects
Stay updated with new AI tools and trends