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Machine Learning (ML) Engineer Career Program

A 4-month program that trains you to build, evaluate, and deploy machine learning models, starting from your first line of Python. The sequence is deliberate: Python first, then the statistics and mathematics that make ML make sense, then core machine learning, then the cloud skills to ship models into production with AWS SageMaker and Docker. Every module closes with milestone projects: spam detection, house and car price prediction, heart disease classification, a fake review detector built with BERT, and a churn model trained, containerized, and deployed as a live API. You graduate with a GitHub portfolio of working models, a deployed end-to-end ML pipeline, a 15-day job bootcamp behind you, and a professional skills track that ran from week one. No coding or math background needed. We start at zero and build in order: each module earns the next. If you can commit four focused months, you can leave as an ML engineer.

Intermediate Lvl
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4 months +1 format
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Livestream & In-person
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Call Duration:20 Mins
What to expect on call?

Your questions answered, specific guidance and support.

This is a Career Program

At a Glance

A snapshot of what makes this course standout.

7 modules in a deliberate order: Python, then math, then machine learning, then cloud deployment. Each module earns the next.

100% hands-on: every module closes with milestone projects that ship to your GitHub.

Core ML coverage: regression, decision trees, KNN, clustering, Random Forest and ensembles, model evaluation and optimization.

The math that powers ML taught for intuition: statistics, probability, and hypothesis testing on real health and business datasets.

Cloud deployment track most ML courses skip: AWS SageMaker, Docker, and real-time inference APIs.

Two capstones: a BERT-powered fake review detection system, and an end-to-end churn pipeline deployed on SageMaker.

15-day job bootcamp: daily mock interviews, ML interview questions, whiteboard challenges, and placement drives.

Human-Centric Professional Skills track running parallel from week one: communication, resume, LinkedIn, recorded mocks.

Live, mentor-led cohorts by industry experts: 8,000+ professionals trained over 15+ years.

Course completion certificate, placement support through the 20+ hiring-partner network, and lifetime TX Backstage community access.

Prerequisites

Baseline knowledge for this course.

No coding or math background required. We start from zero Python and build the math before the ML. If you can use a laptop, you can enroll.

Learning Formats

Schedules and formats available.

Days

Mon-Fri

Duration

4 months

Time

1.5 hours per session

How to Attend

Available online or in person.

Held at all Techboxx Campuses

Physical classroom experience

What you learn

Overview of topics covered in this course

Kickstart your journey with hands-on Python training, from core syntax and data structures to functions, file handling, and basic automation. You'll learn to think like a programmer, write clean code, and debug efficiently using Jupyter and Colab notebooks. Milestone Practice: Daily coding drills and GitHub version control integration.

Lab Experience

Infrastructure you'll work with hands-on

  • •Python (via Anaconda Distribution) for all coursework
  • •Jupyter Notebook and Google Colab for interactive development
  • •Git and GitHub for version control and your project portfolio

Global

For learners outside the subcontinent

Pricing shared on request

Reach out and our team will walk you through pricing, payment plans and any available offers for this program.

Regional

Accessible region-based pricing

Pricing shared on request

Reach out and our team will walk you through pricing, payment plans and any available offers for this program.

Enterprise

Tailored for teams & organizations

What to Expect?

Personalized consultation, custom training plans tailored to your team, comprehensive progress tracking and reporting, flexible scheduling options, and quote-based pricing designed for your organization's needs.

What you become

Roles and career paths this course opens up

The core role this program is built for. You design, train, evaluate, and deploy ML models, and you own the pipeline that keeps them running in production.

Prepares you for

Certifications & career paths

AWS's foundational AI certification. The cloud module's SageMaker and deployment work aligns directly with its ML workflow domains.
A 4-month career program that takes you from zero Python to deployed machine learning models. The sequence is deliberate: Python first, then the statistics and math that power ML, then core machine learning, then cloud deployment with AWS SageMaker and Docker. It closes with a 15-day job bootcamp, and a professional skills track runs parallel from week one.
Freshers from any degree, career switchers from non-tech backgrounds, people restarting after a break, analysts and developers who want to move into ML, and self-learners stuck between scattered tutorials. Everyone starts at the same place: the first line of Python.
No. Module 1 starts at zero Python and builds daily coding habits. The math module is taught for intuition, not proofs: statistics, probability, and hypothesis testing explained through real datasets, placed deliberately before the ML module so that models make sense instead of feeling like magic.
It is focused. Data science programs spend weeks on SQL, Power BI, and Excel. This program cuts that detour and takes the straight path: Python, math, machine learning, cloud deployment. You go deeper on models and production skills in less time, which is exactly what ML engineer interviews test.
Email spam detection, house and car price prediction, heart disease detection with ROC analysis, social media purchase prediction, a fake review detection system built with BERT, and a churn prediction model trained, containerized with Docker, and deployed on AWS SageMaker as a live API. Every project ships to your GitHub.
Video courses give you information, not skill. Nobody reviews your code, nobody catches the flaw in your model evaluation, and nobody makes you defend your results. This program is live and mentor-led, every module ends with reviewed projects, and the bootcamp makes you explain your work out loud until it is interview-proof.
ML engineers are the people who build and deploy the AI. Every model in production needs someone who trained it, validated it, shipped it, and monitors it. AI tools make that person faster; they do not replace them. Demand for engineers who can take a model from notebook to production is rising, not falling.
Yes. The weekend track runs Saturday and Sunday at 2.5 hours per session, all sessions are recorded, and mentors are available for catch-up support throughout.
We call it Kashmir pricing: a globally relevant curriculum priced for our region. The program lists at Rs 85,000. The launch price is Rs 35,000 one-time, or Rs 40,000 in two installments of Rs 20,000. Same mentors, same labs, same placement support at every price point. Compare the syllabus with metro bootcamps charging three times more; that comparison is the point.
Yes. ML hiring is portfolio-first: working models on GitHub and a deployed pipeline speak before your resume does. Four months from now you can show both, plus bootcamp-polished interview answers. The professional skills track coaches you on presenting the gap with confidence instead of apology.
All sessions are recorded, mentors run regular doubt-clearing sessions, and the cohort structure means you are never learning alone. If life interrupts, we work out a catch-up plan rather than leaving you behind.
Yes, the Techboxx ML Engineer course completion certificate, endorsed by industry mentors. But the portfolio matters more: recruiters click GitHub links before they read certificates, and you will graduate with both.
Machine Learning Engineer, Junior Data Scientist, AI Engineer, MLOps and Cloud ML Engineer, Python Developer on data teams, Python-first Data Analyst, and AI Automation Specialist. The cloud deployment skills open the MLOps-flavored roles most fresh ML graduates cannot access.
100% refund if cancelled 7 or more days before cohort start. 50% refund within the first week of the cohort. No refund after that. Medical or emergency situations are handled case-by-case with credit toward future courses.
Call or WhatsApp us at +91-8899-99-5512, or visit techboxx.one to book a free 1-hour consultation with a Techboxx mentor. No pitch, no pressure: a real conversation about your background, your goals, and whether this program is the right move for you. Seats per cohort are limited, so reach out early.
Have a specific question?
Industry experts with 15+ years of deep experience in tech domains
Round-the-clock learner support to answer queries and solve issues
Access to Techboxx's exclusive learning community and resources

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