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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
www.cinutedigital.com

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

25%

Market growth (2020–2030)

101,000+

Data roles open in India

₹9 LPA

Avg fresher salary (Data Science)

75%

Job satisfaction (surveyed)

32%

India’s share of 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 indicative and may vary by source, 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.

5-Core Curriculum Modules

An industry-aligned syllabus that blends Python, statistics, visualization, and machine learning into a job-ready portfolio.

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Live + GuidedProject-basedInterview PrepPortfolio-Ready
  1. 01

    Python Fundamentals

    Master Python syntax, data types, control flow, functions, and best practices that set the foundation for data science.

    Hands-On LabBest PracticesMentor Tips
  2. 02

    Data Visualization Techniques

    Design insightful charts and dashboards using Matplotlib & Plotly; tell clear, compelling data stories.

    Hands-On LabBest PracticesMentor Tips
  3. 03

    Foundations of Statistics & Probability

    Apply descriptive stats, probability, hypothesis testing, and confidence intervals to drive decisions.

    Hands-On LabBest PracticesMentor Tips
  4. 04

    Machine Learning Implementation

    Build and evaluate supervised & unsupervised models with scikit-learn; metrics, tuning, and validation.

    Hands-On LabBest PracticesMentor Tips
  5. 05

    Integrated Project Development

    Ship an end-to-end portfolio project: data prep → EDA → model → API/demo → lightweight cloud deploy.

    Hands-On LabBest PracticesMentor Tips
Apply Now

*Module order may vary slightly based on cohort needs and instructor discretion.

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-ReadyView details →

# 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-ReadyView details →

# 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-ReadyView details →

# 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-ReadyView details →

# 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-ReadyView details →

# 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-ReadyView details →

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

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  • PS

    Priya Sharma

    Data Analyst · FinTech Startup

    ★★★★★ (5.0)

    “This program transformed my career. I went from basics to building production-ready models in weeks.”

    Offer @ ₹9 LPAVerified Learner
  • RV

    Rahul Verma

    ML Engineer · Product Company

    ★★★★★ (5.0)

    “Hands-on ML projects and mentor feedback made a huge difference. The portfolio review helped me stand out.”

    Portfolio: 3 ProjectsVerified Learner
  • AP

    Ananya Patel

    Fresher · EdTech

    ★★★★★ (5.0)

    “Best investment! Clear roadmap, practical labs, and interview prep—landed my first role right after certification.”

    Joined as AnalystVerified Learner
★★★★★Top-rated ML & Data Science Program in Mumbai

Top Companies Hiring Data Science Professionals

•101,000+ Job Vacancies in India•Pan-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 logo

    TCS

  • Infosys logo

    Infosys

  • Wipro logo

    Wipro

  • Cognizant logo

    Cognizant

  • Accenture logo

    Accenture

  • Capgemini logo

    Capgemini

  • HCLTech logo

    HCLTech

  • IBM logo

    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-ReadyLearn more →

# 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-ReadyLearn more →

# 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-ReadyLearn more →

# 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-ReadyLearn more →

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.

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.

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

See Modules Using These ToolsBook a Free Demo

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

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
Call: +91 788-83-83-788Email UsApply Now

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

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