Admissions are open for the Fall 2026 batches ΓÇö limited seats, apply today! Apply now
Duration
12 Weeks
Mode
Hybrid
Audience
University (BS / MS / PhD)
Certificate
Verified

Neural networks, transformers and applied ML workflows ΓÇö train, evaluate and deploy models with scikit-learn, PyTorch and MLOps tooling.

The Artificial Intelligence & Machine Learning program at ITA Academia is a 16-week, mentor-led track designed around real industry workflows. Every module combines live instruction with guided labs, and ends with a graded deliverable that goes straight into your portfolio.

What makes this course different

  • Project-based learning: you build real, demonstrable work ΓÇö not just slides and quizzes.
  • Industry mentors: taught by practitioners who are actively shipping in their domain.
  • Career systems: CV and portfolio reviews, mock interviews and placement support through our hiring-partner network.
  • Flexible pacing: morning, evening and live-online batches with recorded sessions for revision.

By the end of this course you will be able to

  • Implement supervised & unsupervised algorithms
  • Engineer features and evaluate models rigorously
  • Train neural networks with PyTorch
  • Fine-tune transformer models for NLP
  • Deploy models as APIs with FastAPI & Docker

Certification

Graduates receive an ITA Academia verified certificate of completion and a transcript of assessed projects. Selected students are recommended to hiring partners and internship programs.

What you will learn

  • Implement supervised & unsupervised algorithms
  • Engineer features and evaluate models rigorously
  • Train neural networks with PyTorch
  • Fine-tune transformer models for NLP
  • Deploy models as APIs with FastAPI & Docker

Who should attend

  • BS / MS / MPhil / PhD students and fresh graduates
  • Final-year project and thesis students
  • Professionals switching into a tech career

Prerequisites

Working knowledge of programming and the fundamentals covered in our foundation tracks. Admission is subject to a short technical interview.

Course curriculum · 9 modules

Hands-on sessions, guided labs and a graded assignment covering mathematics for ml.

  • Concepts & live demo
  • Guided lab exercise
  • Assignment & review

Hands-on sessions, guided labs and a graded assignment covering supervised learning.

  • Concepts & live demo
  • Guided lab exercise
  • Assignment & review

Hands-on sessions, guided labs and a graded assignment covering unsupervised learning & clustering.

  • Concepts & live demo
  • Guided lab exercise
  • Assignment & review

Hands-on sessions, guided labs and a graded assignment covering model evaluation & tuning.

  • Concepts & live demo
  • Guided lab exercise
  • Assignment & review

Hands-on sessions, guided labs and a graded assignment covering neural networks with pytorch.

  • Concepts & live demo
  • Guided lab exercise
  • Assignment & review

Hands-on sessions, guided labs and a graded assignment covering computer vision.

  • Concepts & live demo
  • Guided lab exercise
  • Assignment & review

Hands-on sessions, guided labs and a graded assignment covering nlp & transformers.

  • Concepts & live demo
  • Guided lab exercise
  • Assignment & review

Hands-on sessions, guided labs and a graded assignment covering mlops & deployment.

  • Concepts & live demo
  • Guided lab exercise
  • Assignment & review

Hands-on sessions, guided labs and a graded assignment covering capstone research project.

  • Concepts & live demo
  • Guided lab exercise
  • Assignment & review
Dr. Ayesha Khan

Dr. Ayesha Khan

Head of AI & Data Science · ex Careem

PhD in Computer Science with a decade of applied ML experience. Ayesha leads the AI & Data Science faculty and has shipped recommendation and forecasting systems used by millions of riders.

Machine LearningLLM Fine-tuningData Pipelines
BatchStartsScheduleModeSeats
Batch 145 – Artificial Intelligence Jul 01, 2026 Mon-Fri On-Campus 15 Apply
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