Applied intelligence · Upcoming
AI / ML Engineer Foundations
Python for data, statistics, classical ML, project work, and an intro to LLMs. Admissions open after Java, Python, and DevOps batches are running.
Duration
Announced at launch
Early bird till 30 Sep
Classroom
₹31,999/-₹15,999/-
Online · 15% less
₹27,199/-₹13,599/-
Offer valid until 30 September 2026
Live classes
Structured weekday sessions + practice.
Industry projects
Work you can demo in interviews.
Mentorship
Doubt support and code review.
Career support
DSA, resume, and mock interviews.
Who this course is for
People who can write Python and want a serious first ML job path — not a weekend ChatGPT workshop.
Outcome: Own a supervised ML pipeline (data → train → evaluate → demo) and explain model choices in interviews.
Job roles this track targets
Technology stack
Tools you will use
Why this is industry-shaped
- · Waitlist for the first cohort
- · Project-first, notebook-second
- · Clear bridge from Python Full Stack if you want both careers in sequence
Syllabus
Planned curriculum (subject to first-cohort lock)
First cohort syllabus
- · Python for data wrangling
- · Probability and metrics used in hiring tests
- · Supervised learning with scikit-learn
- · Feature work, leakage, evaluation
- · Intro to neural nets and LLMs
- · One end-to-end case study + interview set
Projects
Tabular ML case study
Clean data, train baselines, compare models, and write a clear project README.
Eligibility
- · Open to everyone; Python basics help (or finish our Python track first)
- · Comfort with core maths; we teach the stats that matter
- · Time for assignments, not only lectures
Batch timings
- · Dates announced to waitlist first
Next intake: Waitlist · first cohort after current programmes settle
Included in the fee
- · Waitlist counselling when dates freeze
- · Honest fit-check (we may recommend Python Full Stack first)