AI & Applied Machine Learning
From machine-learning foundations to modern LLM applications.
- Track 06
- 12 weeks
- Live classes + mentorship
- Certificate on completion
From machine-learning foundations to modern LLM applications.
Build a solid understanding of machine learning, then apply it: train and evaluate models, work with deep learning and large language models, and deploy AI features behind APIs in real applications.
Live instructor-led sessions, graded exercises and weekly mentor reviews throughout.
NumPy, Pandas, linear algebra and probability essentials.
Regression, classification, clustering and model evaluation with scikit-learn.
Neural networks, PyTorch basics, NLP and computer vision introductions.
Prompting, embeddings, retrieval-augmented generation and evaluation.
Serving models with FastAPI, Docker and responsible-AI practices.
Build and deploy an applied AI project; portfolio review.
Prerequisites: Basic Python. High-school mathematics is enough to start.
Tell us a little about yourself. Our team replies within one business day with batch dates and next steps.
Core sessions are live, with recordings provided. Mentoring, code reviews and capstone work are always live so feedback is meaningful.
Yes. Learners who complete the program, submit the capstone and pass the final evaluation receive a verifiable certificate of completion.
We don't make blanket guarantees, but we offer portfolio reviews, mock interviews and access to our hiring partner network for learners who meet our performance bar.
Yes. Internships of 8 to 24 weeks are available on these tracks — choose "Internship" on the application form.
SQL, Python for data, Pandas, Power BI/Tableau and storytelling with data for real business problems.
Python fundamentals, Django, REST Framework, front-end integration and deployment to the cloud.
AWS fundamentals, Linux, Docker, CI/CD pipelines, Kubernetes basics and infrastructure-as-code.