Artificial Intelligence and Machine Learning
Learn how modern AI works and build your own machine-learning models, from data preparation to deep learning and large language models.
Starts
Thursday, 10 December 2026
Thursdays & Sundays, 7:00 PM – 9:00 PM
Course overview
A hands-on introduction to artificial intelligence for people who want to build, not just use, AI tools. Starting with Python and data, you will train classic machine-learning models, then move to neural networks, computer vision and large language models.
The course ends with a capstone project on a real dataset, with a strong focus on using AI responsibly in the Bangladesh context.
What you will learn
- Prepare, explore and visualise data with pandas
- Train and evaluate machine-learning models with scikit-learn
- Build neural networks with PyTorch
- Apply AI to images and text, including large language models
- Recognise and reduce bias and privacy risks in AI systems
- Deliver an end-to-end AI project
Syllabus
10 modules · 20 sessions · 40 hours
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Week 1 Python for AI
- Python refresher
- NumPy and pandas
- Jupyter notebooks and Google Colab
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Week 2 Working with data
- Cleaning and transforming data
- Exploratory data analysis
- Visualisation with Matplotlib and Seaborn
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Week 3 Machine-learning fundamentals
- Supervised and unsupervised learning
- Training, validation and test sets
- Evaluation metrics
- Overfitting and underfitting
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Week 4 Regression and classification
- Linear and logistic regression
- Decision trees and random forests
- Model tuning with scikit-learn
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Week 5 Unsupervised learning
- Clustering with k-means
- Dimensionality reduction with PCA
- Anomaly detection
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Week 6 Neural networks and deep learning
- How neural networks learn
- Building models in PyTorch
- Training on a GPU
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Week 7 Computer vision
- Convolutional neural networks
- Image classification
- Transfer learning with pretrained models
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Week 8 Natural language processing and LLMs
- Text processing and embeddings
- Transformers explained
- Prompt engineering
- Building with LLM APIs
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Week 9 Responsible AI
- Bias and fairness
- Privacy and data protection
- AI policy and governance in Bangladesh
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Week 10 Capstone project
- Project scoping
- Building and evaluating your model
- Final presentations
Who should attend
Students in computer science, statistics or engineering, software developers, and data and policy analysts who want practical AI skills.
Prerequisites
Basic Python (variables, loops, functions) and school-level mathematics. A laptop with internet access.