AI & Machine Learning
From Python and statistics to deep learning, NLP, computer vision and Generative AI / RAG systems.
PythonPyTorchLLMsRAG
Siffrum Labs is the learning arm of Siffrum Analytics. We train students and graduates in AI/ML, Data Science, Data Analytics, Software Engineering and Cloud — through job-ready courses, summer trainings, internships and industrial training programs.
Technologies you'll master at Siffrum Labs
Curated by working engineers and analysts at Siffrum Analytics — every module ships with hands-on labs, capstone projects, and certification.
From Python and statistics to deep learning, NLP, computer vision and Generative AI / RAG systems.
Statistics, ML modeling, feature engineering and end-to-end data science workflows on real datasets.
SQL, Excel, Power BI and Tableau — build dashboards and storytelling skills used by analytics teams.
DSA, system design, full-stack web (MERN/PHP), Git/CI and clean coding practices for product teams.
AWS, Azure and GCP fundamentals, containers, Kubernetes and DevOps — built for modern cloud careers.
4–24 week programs with real client problems, mentorship and verified completion certificates.
Pick a track and submit your details — our admissions team gets back within 24 hours.
Live + recorded sessions, hands-on labs and a structured curriculum from industry mentors.
Capstone projects on real datasets and product scenarios you can showcase to recruiters.
Get certified, receive interview prep, and apply for internships within the Siffrum ecosystem.
Cohort-after-cohort metrics that matter to students, parents and recruiters.
Real projects, real datasets, real GitHub repos — the kind recruiters actually open.
A retrieval-augmented chatbot that answers questions from a student's PDF notes, with source citations.
Power BI dashboard on retail sales, with cohort analysis, forecast and category drill-downs.
A Terraform + GitHub Actions pipeline to deploy a containerised app to AWS ECS in under five minutes.
A React + PHP web app for students to manage job applications, deadlines and interview prep notes.
End-to-end ML pipeline with feature engineering, model selection and a deployed REST API.
Computer vision + LLM combo that describes camera scenes for visually-impaired users.
The AI/ML cohort was the first time I actually understood why we use embeddings. The mentor reviewed every PR I made — that level of feedback is rare.
I joined the Data Analytics track with zero SQL experience and finished with a Power BI dashboard I now show in every interview. Got my first analyst offer last month.
Industrial training at Siffrum Labs felt like a real job — daily standups, code reviews, sprint demos. My college report basically wrote itself.
The Cloud track gave me hands-on AWS labs I couldn't find anywhere else for free. Cleared my AWS Cloud Practitioner two weeks after finishing.
Small cohort, real mentor attention, and a capstone I'm genuinely proud of. Everything I wished my college had.
From "I don't know Python" to deploying an ML model in 12 weeks. The pace was challenging but the support made it manageable.
Cohort #12 begins in: