25%
Market Growth (2020–2030)
AI adoption accelerating
Loading header...
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.
comprehensive data science and ai course, machine learning training india, data science jobs, fresher salary ds ml, ai market growth, 200 hour data science program, mentor led projects
Market Growth (2020–2030)
Job Vacancies in India
Average Fresher Salary
Job Satisfaction
India’s Global Market Share
Program Duration
Build a recruiter-ready portfolio with dashboards, models, and pipelines—aimed at Data Analyst, Data Scientist, and ML Engineer roles.
*Figures are indicative and vary by location, skills, and industry.
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.
Ingestion → storage → transformation with SQL, pandas/Polars, and lakehouse basics for reliable datasets.
Feature engineering, CV, hyper-parameter tuning, and leakage-free evaluation with scikit-learn.
Neural networks, CNNs/transfer learning with TensorFlow/Keras; best practices for speed and accuracy.
Modern NLP, prompt engineering, and GenAI patterns to build assistants, summarizers, and content systems.
FastAPI packaging, Docker, CI/CD, experiment tracking (MLflow/DVC), and monitoring in production.
Bias checks, documentation, governance, and risk controls so models are explainable and audit-ready.
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.
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.
An industry-aligned path from scalable data engineering to deep learning, NLP, and production deployments — capped by a portfolio-ready project.
data science ai curriculum, spark hadoop course, deep learning computer vision, nlp generative ai, mlops docker kubernetes, data science portfolio
Master large-scale data wrangling with Apache Spark, Hadoop (HDFS/YARN), file formats (Parquet/ORC), and optimized ETL.
Hypothesis testing, confidence intervals, regression diagnostics, experiment design, and causal insights for business decisions.
CNNs, transfer learning, augmentation, fine-tuning, and evaluation for image classification/detection with Keras/PyTorch.
Classical NLP → embeddings → transformer basics, prompt engineering, evaluation, and text generation safety/guardrails.
Model packaging, Docker & Kubernetes, API serving, basic monitoring, CI/CD, and cloud deploys on AWS/GCP/Azure.
Ship enterprise-grade projects with READMEs, reports, demos, and dashboards that recruiters can run and trust.
*Module order may vary slightly by cohort to maximize outcomes.
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
Develop deep-learning models that flag abnormalities in medical images with explainability.
Real-time anomaly detection for transactions with drift monitoring and alerts.
Personalized ranking using collaborative filtering and content features.
CI/CD for models: versioning, testing, and rollouts with monitoring.
Retrieval-augmented QA with citations and guardrails for safer responses.
Demand & pricing forecasts with rolling backtests and error analysis.
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.
Real reviews from the Comprehensive Data Science & AI — Master Program: end-to-end ML, GenAI, and MLOps with a portfolio recruiters trust.
“This masterclass is the gold standard for DS & ML careers—clean pipelines, reproducible experiments, and measurable impact.”
“The 255-hour depth made me interview-ready. I shipped APIs, dashboards, and CI/CD for an end-to-end ML system.”
“Portfolio-first approach worked. I deployed a TensorFlow model on cloud with monitoring and got offers fast.”
“Great coverage from classical ML to GenAI and MLOps. Drift detection and cost controls impressed interviewers.”
“Readme storytelling + MLflow tracking made my case studies stand out. Highly recommended for career switchers.”
“Mock interviews and ATS keyword mapping were spot on. The program is practical, rigorous, and outcomes-driven.”
“This masterclass is the gold standard for DS & ML careers—clean pipelines, reproducible experiments, and measurable impact.”
“The 255-hour depth made me interview-ready. I shipped APIs, dashboards, and CI/CD for an end-to-end ML system.”
“Portfolio-first approach worked. I deployed a TensorFlow model on cloud with monitoring and got offers fast.”
“Great coverage from classical ML to GenAI and MLOps. Drift detection and cost controls impressed interviewers.”
“Readme storytelling + MLflow tracking made my case studies stand out. Highly recommended for career switchers.”
“Mock interviews and ATS keyword mapping were spot on. The program is practical, rigorous, and outcomes-driven.”
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.
data science jobs India, machine learning engineer hiring, AI careers, analytics roles, data scientist vacancies, MLOps jobs, DS AI placements
*Logos are illustrative of hiring potential. Openings vary by location, tech stack, and experience.
Whether you’re a beginner, analyst, or an experienced professional, this program helps you build a recruiter-ready portfolio in Data Science & AI.
who should enroll data science course, ai ml audience, career switch to data science, working professional upskilling, data analyst to data scientist, mlops deployment skills
Start strong with Python, statistics, ML/DL foundations, and portfolio projects to stand out in interviews.
Upskill to lead AI/ML initiatives—learn experimentation, MLOps, and stakeholder storytelling.
Move beyond BI into predictive modeling, feature engineering, and production pipelines.
Enter the AI industry with curated projects, interview prep, and ATS-optimized resumes.
Ideal for students, working professionals, data analysts, and career switchers targeting roles like Data Scientist, ML Engineer, and Applied AI.
Build production-grade pipelines, dashboards, and deployed ML systems with industry-standard tools—from Python/R/SQL to TensorFlow/PyTorch and AWS SageMaker.
EDA, feature engineering, notebooks, data apps, and production APIs.
Statistics, visualization, and reporting with tidyverse workflows.
Model reliable queries, windows, CTEs, and performance tuning.
Interactive dashboards, storytelling, and KPI drill-downs.
Data models, DAX measures, and enterprise-ready reports.
NNs, CNNs, transfer learning, and efficient TF/Keras pipelines.
Flexible modeling, training loops, and deployment patterns.
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.
Follow these 4 proven steps to move from learner to job-ready DS & AI professional with a portfolio recruiters trust.
Python, Statistics, EDA, supervised & unsupervised ML, Deep Learning, NLP, Time Series, Big Data (Spark) foundations.
End-to-end projects (APIs, dashboards, notebooks) deployed to cloud with READMEs, metrics, and reproducible pipelines.
ATS resume, behavioral & technical mocks, packaging models, simple monitoring, CI/CD & deployment checklists.
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.
Everything about our Comprehensive Data Science & AI program—curriculum, tools, projects, timelines, certification, and career support.
data science faq, ai course questions, machine learning program india, job assistance data science, ds ai certification, ml projects tools duration
Still have questions? Talk to an advisor for a personalized walkthrough of outcomes and placement support.
Enroll now for global certification, job assistance, and a portfolio-first curriculum in Python, ML, Deep Learning, NLP/GenAI, and MLOps.
Flexible schedules • Mentor support • Seats are limited—secure yours today.
