AI Study Tasks
4-week AI learning playlist converted into interactive, trackable tasks.
AI vs ML vs DL basics
Week 1, Day 1Watch intro videos about AI, ML, and Deep Learning. Take notes.
Estimated 90 mins
Python basics – variables & control flow
Week 1, Day 2Start Python course, cover variables, data types, if/else and loops.
Estimated 120 mins
Python functions & practice problems
Week 1, Day 3Write small functions and solve practice problems using loops and functions.
Estimated 90 mins
Lists & dictionaries
Week 1, Day 4Learn Python lists, dictionaries, tuples and basic scripts.
Estimated 90 mins
Install and explore NumPy & Pandas
Week 1, Day 5Set up virtualenv, install NumPy and Pandas and test simple snippets.
Estimated 60 mins
NumPy crash course
Week 1, Day 6Work through a NumPy tutorial: arrays, indexing, reshaping, operations.
Estimated 120 mins
Pandas crash course
Week 1, Day 7Learn DataFrame basics, loading CSVs, filtering and grouping.
Estimated 120 mins
Statistics basics for ML
Week 2, Day 8Mean, variance, standard deviation and basic distributions.
Estimated 90 mins
Probability & Bayes rule intuition
Week 2, Day 9Conditional probability, Bayes rule, correlation vs causation.
Estimated 90 mins
Linear algebra for ML
Week 2, Day 10Vectors, matrices, dot product and matrix multiplication.
Estimated 90 mins
Calculus intuition for ML
Week 2, Day 11Understand derivatives and gradients for optimization.
Estimated 90 mins
Intro to supervised & unsupervised learning
Week 2, Day 12Watch ML course intro and learn about train/validation/test splits.
Estimated 90 mins
First ML model in scikit-learn
Week 2, Day 13Implement linear regression or KNN on a simple dataset.
Estimated 120 mins
Overfitting, underfitting & evaluation metrics
Week 2, Day 14Learn accuracy, precision, recall and F1-score.
Estimated 90 mins
Neural networks basics
Week 3, Day 15Perceptron, activation functions, forward pass concept.
Estimated 90 mins
Deep learning course session
Week 3, Day 16Watch 1–2 lectures on building deep neural networks.
Estimated 120 mins
Build a simple neural network
Week 3, Day 17Use Keras or PyTorch to train a small network on MNIST or similar dataset.
Estimated 120 mins
Convolutional Neural Networks (CNNs)
Week 3, Day 18Understand filters, stride, padding and pooling.
Estimated 90 mins
Build a simple CNN classifier
Week 3, Day 19Train a CNN on an image dataset such as digits or cats vs dogs.
Estimated 150 mins
RNNs and LSTMs
Week 3, Day 20Learn sequence modeling concepts for text and time series.
Estimated 90 mins
Mini project polish
Week 3, Day 21Pick one project and clean code, comments, plots and README.
Estimated 150 mins
Transformers & attention (high level)
Week 4, Day 22Learn what transformers are and why attention is powerful.
Estimated 90 mins
Build a GPT from scratch – theory walkthrough
Week 4, Day 23Skim a 'GPT from scratch' video to understand tokenization, attention and training loop.
Estimated 120 mins
Play with an open-source LLM
Week 4, Day 24Use an LLM (API or local) and test prompts for Q&A and summarisation.
Estimated 90 mins
Learn prompt engineering techniques
Week 4, Day 25Role prompting, step-by-step reasoning, few-shot examples, constraints.
Estimated 90 mins
Create your own prompt library
Week 4, Day 26Organise prompts for coding, learning, automation and writing.
Estimated 120 mins
Explore AI productivity tools
Week 4, Day 27Test multiple AI tools on your daily workflow and compare.
Estimated 120 mins
Review & reflection
Week 4, Day 28Write a 1–2 page summary of what you learned and next topics to study.
Estimated 90 mins