Data Science Program with Machine Learning Specialisation

Master the skill of data-driven intelligence with Meritshot’s 360° Career Assistance & ML focused curriculum for Job Switch

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95%

Placement rate

99LPA

Highest CTC

400+

Hiring Partners

150%

Salary Hike

Secure Positions with the World’s Top Tech & Security Companies

What You will Learn?

Python & R

Tableau & PowerBI

Data Analysis

Machine Learning

Big Data

SQL

Project Management

Why Choose Meritshot?

Upskilling from Meritshot gives you an Unfair Advantage by placing you ahead of the curve.

Master Latest Technologies

Learn Machine Learning tools to boost efficiency, handle large datasets, enable analytics, & effective visualization.

Real-World Interview

On demand Mock interviews with actual tech company hiring managers to prepare you for the toughest questions.

Industry Vetted Curriculum

Targeted training for Data Analysis, Statistics, and AI models at the standards expected by top tech giants.

Expert Mentors & Instructorship

Get trained by Industry Experts from Top Tech Companies globally tailored to your career goals.

360° Career Support

From technical skills to salary negotiation — we guide you every step, with 400+ recruiter connections.

Small Batches, Better Learning

Learn in a limited batch size for focused preparation & understanding

What Learners Say About Us?

Join hundreds of professionals who've transformed their careers with Meritshot.

From mechanical engineering to machine learning, Meritshot gave me the structured pathway I needed. I mastered Python, stats, and ML through real-world projects like predictive maintenance and retail segmentation. Mentorship and mock interviews built my confidence. Today, at Tata Digital, I optimize customer engagement using ML — with an 85% salary jump.

Raghav Mehta

4 yrs exp. | Mechanical Engineer → Data Scientist, Tata Digital

From operations to data science, Meritshot made analytics accessible. I learned SQL, Python, ML, and A/B testing, and built a delivery-time prediction model that became my Swiggy interview highlight. Now, I optimize last-mile delivery with ML. Just a year ago, I couldn’t even write a loop — today, I drive impact at scale.

Sneha Iyer

3 yrs exp. | Business Operations → Data Scientist, Swiggy

I moved from IT troubleshooting to data strategy with Meritshot’s structured program. Weekly coding sprints, mentorship, and resume support gave me the push I needed. My recommendation system project became my portfolio centerpiece. Now, at Flipkart, I build data-driven solutions and earn double my earlier salary.

Kunal Bhasin

5 yrs exp. | IT Support → Data Scientist, Flipkart

Even with an MBA, I felt dependent on analytics teams. Meritshot gave me Python, regression, and storytelling skills to own the data. My LTV prediction project landed me at Nykaa, where I now build models for retention and present insights directly to leadership. From support to strategy — that’s my journey.

Ananya Ghosh

3 yrs exp. | MBA (Marketing) → Data Scientist, Nykaa

Meritshot turned my analytical mindset into a career in data. From SQL to model tuning, I learned hands-on through case studies like telecom churn analysis. Mentors helped me reframe my background as a strength. Today, I work at IBM on energy efficiency modeling, bridging my chemical and data worlds.

Devang Patel

2 yrs exp. | Chemical Engineer → Data Analyst, IBM

From teaching to tech, Meritshot made the impossible possible. I learned Python, stats, and ML step by step with patient mentorship. My student performance prediction project helped me land BYJU’S, where I now use analytics to improve learning outcomes. It’s a surreal but empowering transformation.

Priya Nair

4 yrs exp. | Teacher → Data Scientist, BYJU’S

As a consultant, I had business knowledge but lacked technical depth. Meritshot bridged that gap with SQL, ensemble models, and forecasting. My FMCG demand prediction project boosted my confidence and portfolio. Now at Infosys, I drive global consulting projects with real data science expertise.

Abhishek Jain

6 yrs exp. | Business Consultant → Data Scientist, Infosys

From design to data, Meritshot taught me how to think analytically. I learned Python, ML, and dashboarding, blending my creative skills with analytics. My fashion image classification project clicked with Meesho, landing me a role as a data scientist. Today, I combine design + ML to improve product tagging and search.

Reema Sharma

2 yrs exp. | Graphic Designer → Data Scientist, Meesho

Industry Vetted Curriculum

Boost your Data Science Career to Advanced Level with Machine Learning and Stay Ahead of the Curve

6 Weeks

Overview

This module builds the essential foundation every data scientist needs. You’ll gain hands-on experience in programming, databases, statistics, and analytical tools—ensuring you are job-ready from day one.

What You’ll Learn

1. Python Programming

Variables, data types, loops, functions, error handling.  

Object-Oriented Programming (OOPs): classes, inheritance, encapsulation.  

Libraries: NumPy for numerical operations, Pandas for data manipulation.  

Regex for pattern matching & text analytics.  

2. SQL & Databases

Writing queries (DDL, DML, DQL).  

Joins, subqueries, indexing, schema design.  

Aggregations & window functions.  

Database normalization & optimization.  

3. Excel for Analytics

Statistical, logical, and lookup functions.  

Pivot tables & pivot charts.  

Forecasting, regression analysis, dashboards.  

Scenario modeling & “What-if” analysis.  

4. Statistics & Probability

Descriptive stats: mean, median, mode, variance.  

Probability distributions: normal, binomial, Poisson.  

Hypothesis testing: t-test, z-test, chi-square, ANOVA.  

Inferential statistics & sampling.  

Outcomes

Build a rock-solid foundation in Python, SQL, Excel, and statistics to clean, query, and analyze datasets effectively.

5 Weeks

Overview

Learn how to prepare raw, messy data into structured datasets and turn them into powerful visual insights.

What You’ll Learn

1. Data Preprocessing

Handling missing data, outliers, duplicates.  

Feature scaling & normalization.  

Encoding categorical variables (Label, One-hot).  

Feature engineering for ML readiness.  

2. Data Analysis in Python

Pandas operations: merging, joining, reshaping.  

GroupBy, aggregations, pivoting.  

Exploratory Data Analysis (EDA).  

3. Visualization Libraries

Matplotlib & Seaborn for statistical plots.  

Plotly for interactive charts.  

Advanced charting (heatmaps, pairplots, correlation).  

4. Business Intelligence Tools

Tableau: dashboards, KPIs, data storytelling.  

Power BI: data modeling, reports, and insights.  

Outcomes

Ability to preprocess data, uncover insights, and present them visually through dashboards and BI tools.

7 Weeks

Overview

Dive into the world of machine learning and build models that can classify, predict, and cluster data.

What You’ll Learn

1. Supervised Learning

Linear & logistic regression.  

Decision Trees, Random Forests.  

Gradient Boosting: XGBoost, LightGBM.  

2. Unsupervised Learning

K-Means & hierarchical clustering.  

DBSCAN

Dimensionality reduction: PCA, LDA.  

3. Model Evaluation

Train-test split, cross-validation.  

Confusion matrix, precision, recall, F1 score.  

Bias-variance tradeoff, overfitting/underfitting.  

4. Specialized ML

Time series forecasting: ARIMA, SARIMA, Prophet.  

Recommender systems: collaborative & content-based.  

Outcomes

Ability to build, train, and evaluate ML models for prediction, classification, clustering, and recommendations.

5 Weeks

Overview

Work with large-scale datasets and understand modern cloud-based analytics systems.

What You’ll Learn

1. Big Data Foundations

Introduction to Hadoop ecosystem.

Spark architecture: RDDs, DataFrames.

PySpark for large dataset processing.

2. NoSQL Databases

MongoDB & Cassandra basics.

Querying semi-structured/unstructured data.

3. Cloud Fundamentals

AWS/GCP services: compute, storage, IAM.

Cloud-based data pipelines (ETL).

Batch vs stream processing.

Learning Outcomes

Learn to manage, query, and analyze massive datasets on cloud platforms for enterprise-scale problems.

7 Weeks

Overview

Understand neural networks and apply AI to computer vision, NLP, and generative AI.

What You’ll Learn

1. Neural Networks

Perceptrons, feed-forward nets, activation functions.

Backpropagation & optimization.

2. Computer Vision (CV)

CNN architectures (LeNet, VGG, ResNet).

Image classification & object detection.

Transfer learning.

3. Natural Language Processing (NLP)

Text preprocessing: tokenization, stemming, lemmatization.

Embeddings: TF-IDF, word2vec, BERT basics.

4. Generative AI

Autoencoders & GANs.

Intro to LLMs & prompt engineering.

Applied GenAI use cases.

Learning Outcomes

Build AI-powered projects for image, text, and generative tasks that showcase cutting-edge skills.

4 Weeks

Overview

Prepare to work like a real data science professional—deploying models and collaborating in teams.

What You’ll Learn

1. Collaboration Tools

Git, GitHub for version control.

Jira & Trello for project management.

2. MLOps Basics

Model deployment with Flask APIs.

Docker & containerization.

CI/CD for ML pipelines.

Model monitoring & drift detection.

3. AI Productivity Tools

Using ChatGPT, Bard for data analysis.

Automating workflows with AI-driven tools.

Learning Outcomes

Learn how to deploy ML models in production, collaborate effectively, and leverage AI tools for productivity.

6 Weeks

Overview

Apply everything you’ve learned in real-world projects and specialize in your chosen industry domain.

What You’ll Learn

1. Domain Tracks (Choose One)

Banking & Finance → Churn analysis, fraud detection, credit risk modeling.

E-Commerce & Marketing → Recommendation systems, campaign effectiveness.

Healthcare & Pharma → Patient data insights, predictive diagnosis.

HR & Operations → Attrition modeling, workforce optimization.

2. Capstone Project

End-to-end ML project from data collection to deployment.

Use case aligned with industry demand.

3. Career Sprint

Resume & LinkedIn optimization.

Mock interviews (technical + HR).

Access to 400+ hiring partners.

Learning Outcomes

Graduate with job-ready portfolio projects, domain specialization, and placement support to land your dream role.

Dowload Curriculum

Build Capstone Projects with Real-world Data

Testify your Data Science skills by building high end ML pipelines & real time projects

Domain Specialization Projects

Banking, Finance & Insurance

Churn Prediction Model - Identify customers likely to leave a bank using ML.

Fraud Detection System - Build anomaly detection for financial transactions.

Risk-Reward Analysis - Apply statistical models to analyze investment portfolios.

Stock Market Prediction - Time-series forecasting for stock price movement.

E-commerce & Marketing

Customer Lifetime Value Analysis - Segment customers & predict high-value ones.

Ad Campaign Effectiveness - Analyze digital ads performance & ROI.

Recommendation Engine - Build ML-based recommendation systems for products.

Dynamic Pricing Model - Implement demand-based pricing strategies.

Healthcare & Pharma

Patient Risk Prediction - Predict likelihood of chronic diseases (e.g., diabetes).

Medical Image Classification - Classify X-rays & MRIs using CNN.

Pharma Sales Forecasting - Demand forecasting for drug distribution.

Provider Analytics - Analyze hospital resource utilization.

Human Resources & Operations

Attrition Analysis - Predict employee churn using HR datasets.

Promotion Prediction Model - ML model to forecast promotion eligibility.

Workforce Productivity Analysis - Track employee efficiency via data analytics.

Resource Optimization - Optimize staffing needs using predictive analytics.

Capstone & Mini Projects

End-to-End ML Pipeline Deployment - Deploy ML models on AWS with Flask/Django APIs & MLOps monitoring.

Market Basket Analysis for E-commerce - Use Apriori/FP-Growth to recommend cross-selling strategies.

Industry Case Studies

Climate & Food Supply Chain - Predict food security risks with ML.

Keyword Analysis for Google Ads - Optimize ad performance using NLP.

Quora Insincere Question Detection - NLP for harmful content moderation.

Cab Trip Duration Prediction - Improve ridesharing logistics with ML.

Dynamic Product Pricing - Predict optimal pricing for online sellers.

Demand Forecasting for E-commerce - Optimize inventory & supply chains.

Customer Recommendation System - Personalized product suggestions.

Traffic Sign Recognition (CNN) - Enhance autonomous driving with CV.

Mini Projects

Entiment Analysis of Tweets (NLP)

Credit Scoring Model for Banks

Netflix-style Movie Recommendation System

Spam & Phishing Email Classifier

Libraries & Tools Covered

Gain hands-on expertise with 40+ industry-standard tools, programming languages, and frameworks used by top Data Science & AI professionals worldwide.

Get in Touch

Our Expert Mentors

With Highly Experienced Instructors & Mentors you are in SAFE Hands

Chintada Abhilash

Data Science leader

Data Science leader with 7+ years of experience in AI & ML, driving impactful solutions from predictive analytics to automation. Skilled in building scalable models and advanced algorithms, he has led teams to deliver data-driven business outcomes. Abhilash is passionate about turning data into actionable insights and mentoring the next generation of innovators.

Heena Arora

Data Scientist

Data Scientist at PwC with 3+ years of experience in predictive modeling, advanced analytics, and large-scale data solutions. Previously at Amazon, she gained expertise in machine learning and process optimization. Heena specializes in transforming raw data into business insights that drive strategic impact.

Saurabh Daund

AI & Data Science professional

AI & Data Science professional with 5+ years of expertise in NLP, Generative AI, LLMs, and intelligent system design. He has built scalable, AI-driven products that enhance business performance and user experience. Saurabh blends technical depth with practical problem-solving to deliver innovative AI solutions.

Saadh Khan

Investment Banking

With 8+ years in AI & ML, Saadh has led end-to-end projects across industries, from predictive modeling to scalable AI deployment. He brings expertise in advanced analytics and data-informed decision-making. Passionate about innovation, he creates AI solutions that deliver measurable business growth.

Chalsee Choudhary

Data Scientist

Software Developer at PwC with 5 years of experience in building efficient, user-focused applications. Formerly a Data Scientist at Accenture, she combined analytics and ML to solve complex business challenges. Chalsee now integrates her development and data expertise to create impactful technology solutions.

Chintada Abhilash

Data Science leader

Heena Arora

Data Scientist

Saurabh Daund

AI & Data Science professional

Saadh Khan

Investment Banking

Chalsee Choudhary

Data Scientist