Machine Learning with Python – Practical Models & Real-World Projects

Master the fundamentals and advanced concepts of Machine Learning using Python. Learn how to build, train, and evaluate predictive models with hands-on coding and real-world datasets, preparing you for high-demand AI & ML roles.

Cohort Info

Key Highlights

Mode of Learning: Hybrid (Online ILT + Optional In-person Labs)
Number of Modules: 2 (Core + Capstone Project)
Language of Instruction: English
Mapped to NASSCOM SSC/Q8101 NOS for AI/ML Developers.
End-to-end ML pipeline: data preprocessing, model building, evaluation, and deployment basics.

Course Curriculum

Modules designed to meet current industry standards.

01

Machine Learning Foundations

Data preprocessing, exploratory analysis.
Supervised & unsupervised algorithms.
Model evaluation metrics.

02

Applied Machine Learning Project

Real-world predictive analytics project.
Classification model for business decision-making.
Model optimization and basic deployment.

What You’ll Learn

Essential Skills & Tools for Leading Projects in the Digital Age

Need to know more?

Get to know the course in depth by downloading the course brochure

Need to know more?

Get to know the course in depth by downloading the course brochure

Need to know more?

Get to know the course in depth by downloading the course brochure

What Our Learners Say: Read Real Outcomes, Real Voices

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Real People. Real Results

Real stories of career growth, skill mastery, and success after MSM Grad programs.

30% Salary Hike

I joined in order to transform buzzwords into delivery. The Banking Sandbox was the difference; I mapped the stakeholder handoffs and prototyped a tokenized refund flow with simple smart contract logic. The executive hybrid format worked for my release schedule. We were honest about controls and audit trails not just demos during the 144 hours of live instruction.

40% Salary Hike

Tech and regulation were linked in the curriculum. I was able to create rule sets that we could actually uphold with the aid of risk-modeling labs and case work on KYC/AML scenarios. I created a workflow for gathering evidence and a small dashboard for alerts, which our reviewers used. I’m not a developer because of the blockchain projects, but I can assess vendors more critically and schedule changes to comply with regulations.

25% Salary Hike

I wasn’t content with theory. I completed three small projects in the Blockchain Lab: a dashboard for transaction metrics, a simple smart contract with unit tests, and a payments mock on a testnet. In addition to code, the mentors pushed for documentation and threat assumptions. I’ve been shortlisted for two product/engineering internships because I can explain design trade-offs, and my GitHub now displays end-to-end work.

25% Salary Hike

Since I’m not a programmer, I relied on the business-first framing and executive hybrid schedule. I was able to create a strong business case for a lending workflow by using the six implemented FinTech use cases, which covered costs, risks, and the areas where blockchain adds value (and where it doesn’t). While I was in charge of compliance and metrics, my classmate, who worked on the contract code, co-authored our capstone. Interviews were easier because I could display results rather than just slides.

Real People. Real Results

Real stories of career growth, skill mastery, and success after MSM Grad programs.

30% Salary Hike

I joined in order to transform buzzwords into delivery.” The Banking Sandbox was the difference; I mapped the stakeholder handoffs and prototyped a tokenized refund flow with simple smart-contract logic. The executive hybrid format worked for my release schedule. We were honest about controls and audit trails—not just demos—during the 144 hours of live instruction. Although we’re still improving, our incident and chargeback playbooks are now more transparent.

40% Salary Hike

25% Salary Hike

Designed for Ambitious Professionals

Roles Offered

Salary Growth Potential

ML engineer demand is growing at 40% YoY globally (LinkedIn Jobs Report).

Top Salary Bracket

Top Hiring Companies

Designed for Ambitious Professionals

Roles Offered

Salary Growth Potential

ML engineer demand is growing at 40% YoY globally (LinkedIn Jobs Report).

Top Salary Bracket

Top Hiring Companies

Areas of Study

Areas of Study