Master Program in Machine Learning & Data Science with Python

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Become industry-ready with Python, NumPy, Pandas, Data Visualization, scikit-learn, model building, API integration, and cloud deployments. Build portfolio projects and earn a QR-verified certificate.

Curriculum includes EDA best practices, train/validation workflows, metrics, feature engineering, lightweight MLOps (environments, reproducibility), and deployment patterns.

View Curriculum
  • 80% practical labs with mentor feedback
  • Supervised/unsupervised ML with scikit-learn
  • Portfolio projects with docs & GitHub
  • Deployments on cloud + basic MLOps
★★★★★#1 Mumbai’s Premium Training Institute

Why Invest in Machine Learning & Data Science?

Data is the new oil-and Python is the engine powering AI, analytics, and automation across industries.

machine learning market growth, data science jobs India, data analyst salary, ML career trends, Python analytics demand

0%

Market growth (2020–2030)

0+

Job Vacancies in India

0 LPA

Data Science freshers’ average salary

0%

Job Satisfaction

0%

India’s share in the global market

Growing adoption across FinTech, Healthcare, Retail, and SaaS is accelerating demand for Python-first ML engineers, data analysts, and MLOps practitioners.

*Figures are sourced from the program brochure and are indicative; they may vary by role, skills, and location.

Advanced Data Science: A Complete Overview

A mentor-led, job-ready journey through Python, Data Visualization, Statistics & Probability, and Machine Learning — built around hands-on labs and real portfolio projects.

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95 Hours4 CertificatesHands-on ProjectsNo Prerequisites100% Job-Ready

This Hero Program blends theory with practice so you can confidently analyze data, build models, and ship real demos. You’ll learn to structure datasets, visualize insights, apply statistical reasoning, and implement machine learning algorithms in Python. Each module ends with a guided mini-project and code review to ensure you’re job-ready for data-driven roles.

What You’ll Learn

  • Python foundations → EDA → feature engineering
  • Visualizations with Matplotlib & Plotly
  • Statistics & Probability for inference and A/B testing
  • ML with scikit-learn: supervised & unsupervised
  • Model evaluation, metrics, and fair comparison
  • Lightweight MLOps: environments, reproducibility, deploy

Career Paths

Data Analyst • ML Engineer • Data Scientist

Toolchain

Python • NumPy • Pandas • scikit-learn

Deliverables

3+ portfolio projects with docs & demos

Includes mentor guidance, interview prep, resume & LinkedIn polishing, and placement assistance for relevant roles.

Apply Now

*Outcomes depend on practice, project quality, and interview performance.

12-Core Curriculum Modules

Industry-aligned syllabus spanning Python, NumPy/pandas, Matplotlib/Seaborn, Statistics, and Machine Learning with rigorous EDA and validation.

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  1. Python Programming Fundamentals

    • History & setup (Jupyter), syntax, variables, data types, operators, input/print, strings, and clean coding foundations.

    Outcomes: hands-on labs, assessment checklists, and take-home exercises for mastery.

  2. Control Flow & Core Data Structures

    • If/elif/else, logical ops, loops; lists, tuples, sets, dictionaries with indexing/slicing, CRUD, and common methods.

    Outcomes: hands-on labs, assessment checklists, and take-home exercises for mastery.

  3. Functions, Recursion, File I/O & Modules

    • Defining/calling functions (args, scope), recursion, exception handling, open/read/write files, stdlib & custom modules.

    Outcomes: hands-on labs, assessment checklists, and take-home exercises for mastery.

  4. Object-Oriented Programming in Python

    • Classes/objects, instance/class vars & methods, inheritance (single/multiple), polymorphism, encapsulation, properties.

    Outcomes: hands-on labs, assessment checklists, and take-home exercises for mastery.

  5. NumPy for Scientific Computing

    • Arrays vs lists, creation (1D/2D/nD), indexing/slicing, reshaping/broadcasting, random, math/linear algebra utilities.

    Outcomes: hands-on labs, assessment checklists, and take-home exercises for mastery.

  6. Data Analysis with pandas & EDA

    • Series/DataFrame, import/export (CSV/Excel/JSON), cleaning (missing/dupes), filter/sort, groupby/merge/pivot, EDA.

    Outcomes: hands-on labs, assessment checklists, and take-home exercises for mastery.

  7. Data Visualization with Matplotlib

    • Figure/Axes, line/bar/pie, hist/box/heatmap/3D, labels/legends/annotations, simple animations & interactive widgets.

    Outcomes: hands-on labs, assessment checklists, and take-home exercises for mastery.

  8. Advanced Visualization with Seaborn

    • Themes/palettes, dist/KDE/rug, pair/joint plots, categorical (strip/box/violin/swarm), heatmaps/clustermaps, FacetGrid.

    Outcomes: hands-on labs, assessment checklists, and take-home exercises for mastery.

  9. Statistics & Probability Essentials

    • Descriptive stats, hist/box plots, probability rules & Bayes, discrete/continuous distributions (binomial, normal, etc.).

    Outcomes: hands-on labs, assessment checklists, and take-home exercises for mastery.

  10. Sampling, Hypothesis Tests & Regression

    • Sampling & CLT, confidence intervals, z/t/chi-square/ANOVA, correlation (Pearson/Spearman), simple linear regression.

    Outcomes: hands-on labs, assessment checklists, and take-home exercises for mastery.

  11. ML Foundations & Data Preprocessing

    • Supervised vs unsupervised, ML workflow; missing handling, scaling, encoding, train/val/test split; quick model demo.

    Outcomes: hands-on labs, assessment checklists, and take-home exercises for mastery.

  12. Core ML Algorithms & Model Validation

    • Regression (linear/poly, ridge/lasso); classification (logistic, KNN, trees, RF, SVM); CV, metrics (MSE, R², AUC, F1).

    Outcomes: hands-on labs, assessment checklists, and take-home exercises for mastery.

Apply Now

Tools & Technologies You'll Master

Master the essential Python data stack for analytics and machine learning — from data wrangling to model training and visualization.

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Python Data StackEDA & VisualizationModeling & MetricsNotebook-first Workflow
  • Python

    Primary language for ML & data workflows

  • Pandas

    Data wrangling, cleaning & feature prep

  • NumPy

    Fast arrays, math & vectorized operations

  • Scikit-Learn

    Core ML algorithms, pipelines & metrics

  • Matplotlib

    Publication-ready charts & plots

  • Seaborn

    Statistical visuals & quick EDA

  • Jupyter Notebook

    Interactive notebooks for experiments

  • SQL

    Query, join & aggregate data at source

*Tooling may be extended with Plotly, FastAPI, Docker, or cloud notebooks based on cohort needs.

Your Data Science Career Roadmap

Follow these 4 proven steps to move from learner to job-ready Data Science professional with a portfolio recruiters trust.

Program Duration
~ 10–14 Weeks
95+ hours guided learning
Portfolio Projects
3+
Deployed & documented
Target CTC
₹8–15 LPA
Role & location vary
  1. 1
    Job-Ready Foundations

    Complete the 95-Hour Data Science Hero Program

    Master Python, statistics, NumPy, Pandas, data wrangling, SQL, EDA, and practical visualization for business insights.

  2. 2
    Portfolio & GitHub

    Build 3 Portfolio Projects

    Ship an analytics dashboard, a time-series forecasting model, and a classification/NLP project. Document on GitHub with READMEs and CI checks.

  3. 3
    Cloud & MLOps

    Deploy & Operationalize (MLOps)

    Serve models via FastAPI, containerize with Docker, and deploy to cloud (AWS/GCP). Add monitoring, metrics, and API docs.

  4. 4
    Offer & Onboarding

    Career Prep & Land a Data Role

    Resume revamp, ATS keywords, mock interviews, case studies, and SQL/ML refresher. Target ₹8–15 LPA roles (Data Analyst, ML Engineer, Data Scientist).

Get Personalized Roadmap

Learn from anywhere. Your journey to a Data Science career starts here.

Real-World Projects You’ll Build

Build a portfolio recruiters love: hands-on Python, Data Science, and Machine Learning projects with clean code, clear storytelling, and business impact. Each project is production-minded and interview-ready.

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# Data Analysis Dashboard (Executive Insights)

Transform messy business data into interactive dashboards that reveal KPIs, trends, and anomalies. Use Python to clean, join, and visualize data for decision-makers.

  • Design KPI scorecards and cohort views
  • Build drill-downs for product, region, and channel
  • Ship a shareable dashboard and executive summary
PythonPandasPlotlyFastAPISQL
Job-Ready • Portfolio-Ready

# Sales Forecasting Model (Time-Series ML)

Engineer a robust forecasting pipeline using classical and ML approaches to predict weekly sales with confidence intervals and scenario analysis.

  • Feature engineering for seasonality & promotions
  • Compare ARIMA/Prophet vs. ML regressors
  • Backtesting & error analysis (MAE, MAPE, SMAPE)
scikit-learnProphetNumPyMatplotlib
Job-Ready • Portfolio-Ready

# Customer Segmentation (Clustering & RFM)

Segment customers with unsupervised learning to personalize campaigns and improve retention using explainable, data-driven cohorts.

  • RFM scoring + K-Means/DBSCAN comparison
  • Silhouette evaluation & interpretability
  • Actionable cohort playbooks for marketing
scikit-learnPandasSeabornUmap-learn
Job-Ready • Portfolio-Ready

# Churn Prediction (Classification Pipeline)

Predict user churn with an end-to-end ML pipeline—balanced training, model selection, and business-friendly, explainable results.

  • Data imbalance handling (SMOTE/weights)
  • ROC-AUC, PR-AUC, and calibration reporting
  • SHAP-based explanations & retention levers
scikit-learnXGBoostSHAPMLflow
Job-Ready • Portfolio-Ready

# NLP Insights (Reviews & Sentiment)

Mine product reviews to extract topics, sentiment, and pain points. Turn qualitative text into quantifiable product insights.

  • Text cleaning & embeddings
  • Topic modeling with coherence checks
  • Aspect-based sentiment & insight report
spaCyNLTKSentence-TransformersUMAP
Job-Ready • Portfolio-Ready

# End-to-End AI App (Data → Model → API → UI)

Ship a production-ready mini-application: automated data flows, trained model, REST API, and a lightweight UI with auth and monitoring.

  • Orchestrate pipelines & model registry
  • Serve predictions via FastAPI
  • Observability & CI/CD with tests
FastAPIDockerPyTestGitHub ActionsVercel
Job-Ready • Portfolio-Ready

These industry-aligned data projects reflect real metrics, clean engineering practices, and clear communication—exactly what hiring managers look for in Data Analysts, ML Engineers, and Data Scientists.

*Outcomes and tools may vary by dataset, domain, and role.

What Our Students Say

Real outcomes from learners who completed our mentor-led Machine Learning & Data Science program.

5.0/5 · 3 reviews

data science course reviews, machine learning student testimonials, placement success stories, ML portfolio feedback, Python training ratings

Google logoEXCELLENTBased on 289 reviews

Prathik Singh

2025-06-27Google

Google logoVerified

I had the opportunity to intern at Cinute, and it has been a great learning experience... I worked on data analysis in Excel, created dashboards, and explored Power BI & Tableau. The quality of teaching is so good...

Trustindex verifies source on Google / platform verifies identity where applicable.

YASH

2025-06-27Google

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Trustindex verifies source on Google / platform verifies identity where applicable.

Sujal Vaity

2025-06-27Google

Google logoVerified

Trustindex verifies source on Google / platform verifies identity where applicable.

bhumika Ankush

2025-06-27Google

Google logoVerified

The subjects taught are relevant and help prepare students for real-world challenges.

Trustindex verifies source on Google / platform verifies identity where applicable.

Vedang Mohit

2025-06-27Google

Google logoVerified

The subjects taught are relevant and help prepare students for real-world challenges.

Trustindex verifies source on Google / platform verifies identity where applicable.

Aryan Prasad

2025-06-27Google

Google logoVerified

It's a good opportunity to do course and learn coding languages... good mentors.

Trustindex verifies source on Google / platform verifies identity where applicable.

Dhruv Salvi

2025-06-27Google

Google logoVerified

Helped me to learn and gain a lot of knowledge and skills growth throughout, humble and good communicating staff and members.

Trustindex verifies source on Google / platform verifies identity where applicable.

Bhuvan Sharma

2025-06-27Google

Google logoVerified

Good information provided by the domain providers, very good at communicating and humble...

Trustindex verifies source on Google / platform verifies identity where applicable.

Sahil Bhaye

2025-06-27Google

Google logoVerified

Trustindex verifies source on Google / platform verifies identity where applicable.

Durgesh parab

2025-06-27Google

Google logoVerified

It is best company to get experience... I’m learning full-stack with highly talented staff...

Trustindex verifies source on Google / platform verifies identity where applicable.

Prathik Singh

2025-06-27Google

Google logoVerified

I had the opportunity to intern at Cinute, and it has been a great learning experience... I worked on data analysis in Excel, created dashboards, and explored Power BI & Tableau. The quality of teaching is so good...

Trustindex verifies source on Google / platform verifies identity where applicable.

YASH

2025-06-27Google

Google logoVerified

Trustindex verifies source on Google / platform verifies identity where applicable.

Sujal Vaity

2025-06-27Google

Google logoVerified

Trustindex verifies source on Google / platform verifies identity where applicable.

bhumika Ankush

2025-06-27Google

Google logoVerified

The subjects taught are relevant and help prepare students for real-world challenges.

Trustindex verifies source on Google / platform verifies identity where applicable.

Vedang Mohit

2025-06-27Google

Google logoVerified

The subjects taught are relevant and help prepare students for real-world challenges.

Trustindex verifies source on Google / platform verifies identity where applicable.

Aryan Prasad

2025-06-27Google

Google logoVerified

It's a good opportunity to do course and learn coding languages... good mentors.

Trustindex verifies source on Google / platform verifies identity where applicable.

Dhruv Salvi

2025-06-27Google

Google logoVerified

Helped me to learn and gain a lot of knowledge and skills growth throughout, humble and good communicating staff and members.

Trustindex verifies source on Google / platform verifies identity where applicable.

Bhuvan Sharma

2025-06-27Google

Google logoVerified

Good information provided by the domain providers, very good at communicating and humble...

Trustindex verifies source on Google / platform verifies identity where applicable.

Sahil Bhaye

2025-06-27Google

Google logoVerified

Trustindex verifies source on Google / platform verifies identity where applicable.

Durgesh parab

2025-06-27Google

Google logoVerified

It is best company to get experience... I’m learning full-stack with highly talented staff...

Trustindex verifies source on Google / platform verifies identity where applicable.
Google Reviews logo
289
Google Reviews
Public reviews
Sulekha Reviews logo
84
Sulekha Reviews
5.0 average
Justdial Ratings logo
210
Justdial Ratings
Verified users
★★★★★Top-rated ML & Data Science Program in Mumbai

Top Companies Hiring Data Science Professionals

101,000+ Job Vacancies in IndiaPan-India • Product & Services • Startup & Enterprise

Join the ranks of Data Scientists, ML Engineers, and Analytics Professionals at India’s leading product and services companies.

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  • TCS

  • Infosys

  • Wipro

  • Cognizant

  • Accenture

  • Capgemini

  • HCLTech

  • IBM

Data ScientistML EngineerData AnalystMLOps EngineerBI Analyst
Apply for Placement Assistance

*Logos are for illustration of hiring potential. Roles and openings vary by location, skills, and experience.

Who Is This Course For

Whether you’re starting out or leveling up, this program turns Python, Data Science, and Machine Learning skills into measurable career outcomes—portfolio projects, practical tooling, and interview-ready confidence.

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# Beginners & Non-Coders

Start your Data Science journey from zero—learn Python, statistics, and analytics step by step with hands-on practice.

  • No prior coding required
  • Guided projects and mentor feedback
Beginner-Friendly • Job-Ready

# Working Professionals

Upskill with Python-first ML to boost roles in technology, finance, healthcare, marketing, and education.

  • Career-oriented case studies
  • Practical tools: Pandas, SQL, scikit-learn
Beginner-Friendly • Job-Ready

# Intermediate Learners

Go deeper into machine learning, model evaluation, and MLOps to deliver production-ready solutions.

  • End-to-end ML pipelines
  • Model tuning, SHAP, experiment tracking
Beginner-Friendly • Job-Ready

# Students & Career Switchers

Build a job-ready portfolio and transition into high-growth roles like Data Analyst, ML Engineer, or Data Scientist.

  • Portfolio projects recruiters love
  • Interview prep & placement guidance
Beginner-Friendly • Job-Ready

Ideal for Python beginners, working professionals, intermediate learners, and career switchers seeking Data Analyst, ML Engineer, or Data Scientist roles.

*Learning paths adapt by background and pace.

Frequently Asked Questions

Everything you need to know about our mentor-led Machine Learning & Data Science program.

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  • Is prior programming experience required?
    No. We start from Python fundamentals and progressively move into data analysis, visualization, statistics, and ML. Beginners can follow along with mentor support and hands-on labs.
  • What is the duration of the program?
    The program spans ~95 guided hours, typically completed over 8–10 weeks with live sessions, labs, code reviews, and a capstone project.
  • Will I get job placement assistance?
    Yes. You’ll receive resume and LinkedIn polishing, portfolio review, mock interviews, and curated referrals for relevant ML/Data roles.
  • What tools and libraries are covered?
    Python, NumPy, Pandas, Matplotlib/Seaborn, scikit-learn, Jupyter, and SQL. Where relevant, we demo Plotly, FastAPI, or lightweight deploys.
  • Do I get a certificate?
    Yes. You’ll receive a QR-verified certificate from Cinute Digital Pvt. Ltd. upon successful completion of assessments and the capstone.
Still have questions? Contact us

Ready to Launch Your Data Science Career?

Enroll now to get 100% job assistance, 4 global certificates, and a portfolio recruiters love — built with Python, SQL, Machine Learning, and real projects.

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  • Job Assistance
    Resume, mock interviews, referrals
  • Global Certificates
    4 verifiable credentials
  • Project Portfolio
    GitHub + live demos

Secure your seat today. Limited cohorts, mentor-led, flexible schedules.

Prefer WhatsApp? Message us at +91 788-83-83-788