Live Online + Classroom255 HoursProject-basedPlacement Support
Master Program in Comprehensive Data Science & AI
Become industry-ready with Python, Statistics, Machine Learning, Deep Learning, NLP, Time Series, Big Data (Spark), and MLOps. Build portfolio projects and earn a QR-verified certificate.
Curriculum includes Pandas/NumPy, EDA & visualization, model evaluation, feature engineering, pipelines, basic Transformers, cloud deployments, and CI/CD best practices.
Equip yourself for tomorrow’s roles with Python, ML, DL, and data engineering foundations-delivered via mentor-led, project-first learning.
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0%
Market Growth (2020–2030)
AI adoption accelerating
0+
Job Vacancies in India
DA • DS • ML roles
₹0 LPA
Average Fresher Salary
City & role dependent
0%
Job Satisfaction
Impactful problem-solving
0%
India’s Global Market Share
Services • Product • Startups
0+ Hours
Program Duration
Projects + mentorship
Build a recruiter-ready portfolio with dashboards, models, and pipelines-imed at Data Analyst, Data Scientist, and ML Engineer roles.
*Figures are indicative and vary by location, skills, and industry.
Comprehensive Data Science & AI - Master Program Overview
Go end-to-end from data processing to advanced AI deployment. Build a job-ready portfolio in Python, scikit-learn, TensorFlow, NLP/GenAI, and MLOps-guided by industry experts.
255 Hours
Hands-On Projects
Expert Faculty
Prior Exp Helpful
100% Job-Ready
Data Engineering Foundations
Ingestion → storage → transformation with SQL, pandas/Polars, and lakehouse basics for reliable datasets.
Classical ML That Scales
Feature engineering, CV, hyper-parameter tuning, and leakage-free evaluation with scikit-learn.
Deep Learning & Computer Vision
Neural networks, CNNs/transfer learning with TensorFlow/Keras; best practices for speed and accuracy.
NLP & Generative AI
Modern NLP, prompt engineering, and GenAI patterns to build assistants, summarizers, and content systems.
MLOps & Deployment
FastAPI packaging, Docker, CI/CD, experiment tracking (MLflow/DVC), and monitoring in production.
Responsible, Secure AI
Bias checks, documentation, governance, and risk controls so models are explainable and audit-ready.
What you’ll learn (and build)
From EDA & feature engineering to model development, NLP/GenAI, and MLOps, this program emphasizes deployable skills. You’ll ship APIs, dashboards, and reproducible experiments that translate directly to interviews and on-the-job impact.
Business KPIs → dashboards & reports that drive decisions.
Versioned experiments with MLflow/DVC; reproducible baselines.
Performance, drift & cost monitoring with alerting SLAs.
Cloud patterns across AWS/GCP/Azure for scalable training & serving.
Clear READMEs, notebooks, and portfolio storytelling recruiters love.
Keywords: data science and AI course, ML masterclass, deep learning with TensorFlow, NLP and Generative AI, MLOps pipeline, model monitoring, cloud AI solutions, Python data analysis.
12-Module Curriculum
An industry-aligned path spanning SQL & BI to Python, Statistics, ML, R, and modern GenAI-with real projects that recruiters can run and trust.
MySQL DBMS course, Advanced Excel analytics, Power BI training, Tableau storytelling, Python programming, pandas matplotlib seaborn, NumPy, statistics and probability, machine learning with Python, R ggplot2 lm glm, deep learning NLP generative AI, prompt engineering, data science capstone projects
MySQL & SQLAdvanced ExcelPower BITableauPythonStats & ML
*Module order may vary slightly by cohort to maximize outcomes.
Tools & Technologies You’ll Master
Build production-grade pipelines, dashboards, and deployed ML systems with industry-standard tools—from Python/R/SQL to TensorFlow/PyTorch and AWS SageMaker.
Hands-On Stack
8 Core Tools
EDA • BI • DL • MLOps
Deploy Anywhere
Cloud & On-Prem
AWS • GCP • Azure patterns
Outcome
Job-Ready Portfolio
APIs • Dashboards • Models
PythonCore Language
EDA, feature engineering, notebooks, data apps, and production APIs.
RAnalytics
Statistics, visualization, and reporting with tidyverse workflows.
SQLData Backbone
Model reliable queries, windows, CTEs, and performance tuning.
TableauBI & Viz
Interactive dashboards, storytelling, and KPI drill-downs.
Power BIDashboards
Data models, DAX measures, and enterprise-ready reports.
TensorFlowDeep Learning
NNs, CNNs, transfer learning, and efficient TF/Keras pipelines.
PyTorchResearch → Prod
Flexible modeling, training loops, and deployment patterns.
AWS SageMakerMLOps
Training jobs, endpoints, monitoring, and CI/CD integrations.
Master Python, R, SQL, Tableau, Power BI, TensorFlow, PyTorch, and AWS SageMaker to build scalable data science and AI solutions.
Your DS & AI Career Roadmap
Follow these 4 proven steps to move from learner to job-ready DS & AI professional with a portfolio recruiters trust.
Program Duration
~ 12–16 Weeks
255 hours guided learning
Portfolio Projects
3–5
Deployed & documented
Target CTC
₹9–18 LPA
Role & location vary
1
Job-Ready Foundations
Complete the 255-Hour DS & AI Master Program
Python, Statistics, EDA, supervised & unsupervised ML, Deep Learning, NLP, Time Series, Big Data (Spark) foundations.
2
Portfolio & GitHub
Build & Ship an Advanced Portfolio
End-to-end projects (APIs, dashboards, notebooks) deployed to cloud with READMEs, metrics, and reproducible pipelines.
Target Data Scientist, ML Engineer, Applied AI Specialist, or MLOps roles (₹9–18 LPA based on city & stack).
Learn from anywhere. Your journey to a DS & AI career starts here.
Real-World DS & AI Projects
Build production-grade AI systems and data pipelines with clear metrics, governance, and deployability.
data science projects, ai portfolio projects, healthcare ai diagnostic, fraud detection ml, recommendation engine, mlops pipeline deployment, rag question answering, time series forecasting
# Healthcare AI Diagnostic
Develop deep-learning models that flag abnormalities in medical images with explainability.
Transfer learning
Grad-CAM insights
Bias & safety checks
PyTorchTorchVisionOpenCVFastAPI
Portfolio-Ready • Production-Minded
# Financial Fraud Detection
Real-time anomaly detection for transactions with drift monitoring and alerts.
Feature stores
Imbalance handling
Streaming scoring
scikit-learnLightGBMKafkaAirflow
Portfolio-Ready • Production-Minded
# Recommendation Engine
Personalized ranking using collaborative filtering and content features.
Implicit feedback
Cold-start strategy
A/B-like offline eval
FaissImplicitPandasSQL
Portfolio-Ready • Production-Minded
# MLOps Pipeline & Deployment
CI/CD for models: versioning, testing, and rollouts with monitoring.
Model registry
Canary deploy
Data & concept drift
DockerGitHub ActionsMLflowS3
Portfolio-Ready • Production-Minded
# RAG QA Assistant
Retrieval-augmented QA with citations and guardrails for safer responses.
Chunking & indexing
Citations
Eval harness
EmbeddingsVector DBLLMGuardrails
Portfolio-Ready • Production-Minded
# Time-Series Forecasting
Demand & pricing forecasts with rolling backtests and error analysis.
Feature lags/regimes
Cross-validation
Residual diagnostics
statsmodelsProphetPlotlyPandas
Portfolio-Ready • Production-Minded
These industry-aligned projects emphasize reproducibility, evaluation, and clean architecture-ideal for Data Scientist, ML Engineer, and Applied AI roles.
*Scope varies by dataset, domain, and pace.
What Our Students Say
Real reviews from the Comprehensive Data Science & AI - Master Program: end-to-end ML, GenAI, and MLOps with a portfolio recruiters trust.
4.9/5 Average RatingVerified AlumniPortfolio & Offers
EXCELLENT•Based on 289 reviews
Prathik Singh
2025-06-27 • Google
Verified
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...
YASH
2025-06-27 • Google
Verified
—
Sujal Vaity
2025-06-27 • Google
Verified
—
bhumika Ankush
2025-06-27 • Google
Verified
The subjects taught are relevant and help prepare students for real-world challenges.
Vedang Mohit
2025-06-27 • Google
Verified
The subjects taught are relevant and help prepare students for real-world challenges.
Aryan Prasad
2025-06-27 • Google
Verified
It's a good opportunity to do course and learn coding languages... good mentors.
Dhruv Salvi
2025-06-27 • Google
Verified
Helped me to learn and gain a lot of knowledge and skills growth throughout, humble and good communicating staff and members.
Bhuvan Sharma
2025-06-27 • Google
Verified
Good information provided by the domain providers, very good at communicating and humble...
Sahil Bhaye
2025-06-27 • Google
Verified
—
Durgesh parab
2025-06-27 • Google
Verified
It is best company to get experience... I’m learning full-stack with highly talented staff...
Prathik Singh
2025-06-27 • Google
Verified
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...
YASH
2025-06-27 • Google
Verified
—
Sujal Vaity
2025-06-27 • Google
Verified
—
bhumika Ankush
2025-06-27 • Google
Verified
The subjects taught are relevant and help prepare students for real-world challenges.
Vedang Mohit
2025-06-27 • Google
Verified
The subjects taught are relevant and help prepare students for real-world challenges.
Aryan Prasad
2025-06-27 • Google
Verified
It's a good opportunity to do course and learn coding languages... good mentors.
Dhruv Salvi
2025-06-27 • Google
Verified
Helped me to learn and gain a lot of knowledge and skills growth throughout, humble and good communicating staff and members.
Bhuvan Sharma
2025-06-27 • Google
Verified
Good information provided by the domain providers, very good at communicating and humble...
Sahil Bhaye
2025-06-27 • Google
Verified
—
Durgesh parab
2025-06-27 • Google
Verified
It is best company to get experience... I’m learning full-stack with highly talented staff...
289
Google Reviews
Public reviews
84
Sulekha Reviews
5.0 average
210
Justdial Ratings
Verified users
Read independent reviews of our Data Science & AI master program. Alumni highlight reproducible ML pipelines, GenAI, MLOps, deployment, monitoring, and job placements.
High-growth careers across Data Science, Machine Learning Engineering, MLOps, and Applied AI in product & services companies.
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Data ScientistML EngineerData AnalystApplied AI EngineerMLOps Engineer
*Logos are illustrative of hiring potential. Openings vary by location, tech stack, and experience.
Who Is This Course For
Whether you’re a beginner, analyst, or an experienced professional, this program helps you build a recruiter-ready portfolio in Data Science & AI.
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# Students & Fresh Graduates
Start strong with Python, statistics, ML/DL foundations, and portfolio projects to stand out in interviews.
Zero-to-job-ready path
Mentor feedback & reviews
# Working Professionals
Upskill to lead AI/ML initiatives—learn experimentation, MLOps, and stakeholder storytelling.
Impact metrics & dashboards
Deployment checklists
# Data Analysts
Move beyond BI into predictive modeling, feature engineering, and production pipelines.
SQL → ML pipelines
Model evaluation & drift
# Career Switchers
Enter the AI industry with curated projects, interview prep, and ATS-optimized resumes.
Portfolio review
Mock interviews & guidance
Ideal for students, working professionals, data analysts, and career switchers targeting roles like Data Scientist, ML Engineer, and Applied AI.
Frequently Asked Questions
Everything about our Comprehensive Data Science & AI program—curriculum, tools, projects, timelines, certification, and career support.
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Q. Is prior experience required?
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Basic programming and statistics help, but the program includes a structured ramp-up covering Python, data wrangling, and ML fundamentals so motivated beginners can succeed.
Q. What is the total duration?
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Approximately 255 hours of guided learning with 80% hands-on labs, capstone projects, and weekly mentor check-ins.
Q. Do you provide job assistance?
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Yes. You’ll get resume review with ATS keywords, mock interviews, LinkedIn optimization, and curated referrals through our network.
Q. What projects and tools are covered?
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Projects in NLP, computer vision, forecasting, and MLOps. Tools include Python, scikit-learn, PyTorch/TensorFlow, SQL, Spark, Airflow, and AWS for deployment.
Q. Is there a certificate?
▾
Yes. You’ll receive a globally verifiable certificate with QR validation. Guidance is provided to showcase your portfolio on GitHub and LinkedIn.
Still have questions? for a personalized walkthrough of outcomes and placement support.
Ready to Master Data Science & AI?
Enroll now for global certification, job assistance, and a portfolio-first curriculum in Python, ML, Deep Learning, NLP/GenAI, and MLOps.