Become a certified Data Scientist. Learn Python, Machine Learning (scikit-learn), Deep Learning, NLP, SQL, data visualization, and model deployment — build a portfolio of real data projects with placement-ready skills.
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Industry-focused training in Data Science and Machine Learning with hands-on projects using Python, Pandas, NumPy, scikit-learn, TensorFlow, and PyTorch. Learn SQL, data visualization with Tableau and Power BI, model evaluation, model deployment, and MLOps practices. Build a portfolio of real data projects and get placement support for Data Scientist, ML Engineer, and Data Analyst roles.
CDPL’s Data Science program covers Data Wrangling (Pandas, NumPy), Exploratory Data Analysis, Statistical Modeling, Supervised & Unsupervised Learning, Deep Learning (TensorFlow/PyTorch), NLP, Time Series, Model Deployment, MLOps, and SQL for data querying. The curriculum is designed for beginners and working professionals aiming for Data Scientist, ML Engineer, and Data Analyst roles.
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Learn the full data science lifecycle: data engineering, modeling, evaluation, and production deployment. Projects, mentorship and career support included.
Understand supervised & unsupervised learning, model selection, evaluation metrics, and build classical ML models (logistic regression, trees, SVMs) with hands-on labs.
Master data cleaning, transformation, feature creation, and pipelines using pandas, SQL, and best practices to prepare production-grade datasets.
Learn to analyze distributions, correlations, and communicate insights using Matplotlib, Seaborn and interactive dashboards to influence business decisions.
Build, train and tune neural networks for image, text and tabular data using PyTorch/TensorFlow — covering CNNs, RNNs, transformers and best optimization practices.
Model time-dependent data with ARIMA, Prophet and modern deep learning approaches for robust forecasting and anomaly detection in real-world systems.
Deploy models to production with Docker, REST endpoints, CI/CD pipelines and monitor model performance using proper logging, retraining strategies and versioning.
Gain statistical intuition: hypothesis testing, A/B testing, causal inference and confidence intervals to make data-driven product decisions.
Implement real-world NLP pipelines (tokenization, embeddings, transformers) and CV tasks (object detection, segmentation) with practical projects.
Complete end-to-end capstones, prepare a portfolio, get interview coaching and hiring connections to land roles as Data Scientist, ML Engineer, or Researcher.
Ready to level up? Start building production-ready ML systems today.
Choose from our comprehensive range of courses designed to make you job-ready with hands-on projects and expert mentorship.
Master Machine Learning & Data Science with Python in our Hero Program! Hands-on projects, expert mentorship & job-ready skills. Enroll now & launch your tech career!
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Dive into Deep Learning, NLP & Generative AI! Master neural networks, text processing & AI creation with hands-on projects. Enroll now & lead the AI revolution!
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Elevate your career with Advanced Data Science & Machine Learning Masterclass! Deep-dive into algorithms, big data & AI. Expert-led, project-based. Enroll today!
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Unlock expertise in Comprehensive Data Science & AI Master Program! From ML to deep learning, big data & ethics. Hands-on, industry-aligned. Enroll now & shape the future!
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Master Machine Learning Algorithms using Python Programming! Implement regression, classification, clustering & more with scikit-learn. Hands-on code, real projects. Enroll now!
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Master Machine Learning & Data Visualization using R Programming! Explore ggplot2, tidyverse, ML models & interactive dashboards. Hands-on projects. Enroll now & excel in data!
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Master Python Programming from absolute basics all the way to advanced and professional-level concepts! Dive deep into Python syntax, data structures, object-oriented programming, functional programming, automation scripting, and real-world problem-solving through engaging, hands-on projects that reinforce every concept.
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Structured for maximum learning and career readiness.
Python environment setup, core programming concepts, data types, control structures, functions, and an introduction to Data Science workflows and ethics.
Advanced Pandas for data manipulation, NumPy for numerical computing, data cleaning techniques, and exploratory data analysis (EDA) principles.
Probability, hypothesis testing, statistical inference, and creating insightful visualizations using Matplotlib, Seaborn, and Plotly.
Regression (linear, logistic, polynomial), classification algorithms (Decision Trees, SVM, KNN), model evaluation metrics, and cross-validation with Scikit-learn.
Clustering (K-Means, DBSCAN), dimensionality reduction (PCA, t-SNE), association rules, and advanced feature selection/engineering techniques.
Bagging, Boosting (Random Forest, XGBoost, LightGBM), stacking, hyperparameter tuning, and deploying models using Flask/FastAPI on Heroku/AWS.
ARIMA, Prophet, LSTM for forecasting, anomaly detection, and introduction to reinforcement learning concepts with real-world case studies.
Spark MLlib for distributed computing, Dask for parallel processing, handling large datasets, and MLOps basics with MLflow.
Full end-to-end industry-level project, portfolio optimization, mock interviews, resume building, and career strategies in ML/DS roles.
Join thousands of learners who advanced their careers through hands-on Data Science & Machine Learning training. See how alumni moved into data roles, shipped models to production, and boosted their earnings.
EXCELLENT•Based on 289 reviews2025-06-27 • Google
VerifiedI 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...
2025-06-27 • Google
Verified—
2025-06-27 • Google
Verified—
2025-06-27 • Google
VerifiedThe subjects taught are relevant and help prepare students for real-world challenges.
2025-06-27 • Google
VerifiedThe subjects taught are relevant and help prepare students for real-world challenges.
2025-06-27 • Google
VerifiedIt's a good opportunity to do course and learn coding languages... good mentors.
2025-06-27 • Google
VerifiedHelped me to learn and gain a lot of knowledge and skills growth throughout, humble and good communicating staff and members.
2025-06-27 • Google
VerifiedGood information provided by the domain providers, very good at communicating and humble...
2025-06-27 • Google
Verified—
2025-06-27 • Google
VerifiedIt is best company to get experience... I’m learning full-stack with highly talented staff...
2025-06-27 • Google
VerifiedI 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...
2025-06-27 • Google
Verified—
2025-06-27 • Google
Verified—
2025-06-27 • Google
VerifiedThe subjects taught are relevant and help prepare students for real-world challenges.
2025-06-27 • Google
VerifiedThe subjects taught are relevant and help prepare students for real-world challenges.
2025-06-27 • Google
VerifiedIt's a good opportunity to do course and learn coding languages... good mentors.
2025-06-27 • Google
VerifiedHelped me to learn and gain a lot of knowledge and skills growth throughout, humble and good communicating staff and members.
2025-06-27 • Google
VerifiedGood information provided by the domain providers, very good at communicating and humble...
2025-06-27 • Google
Verified—
2025-06-27 • Google
VerifiedIt is best company to get experience... I’m learning full-stack with highly talented staff...
Apply your learning through practical, industry-relevant projects.
Build real-world projects to strengthen your portfolio.
Predict equipment failure using time-series data and deep learning.
Technologies & Skills
Identify and predict customers likely to leave a telecom company.
Technologies & Skills
Develop a deep learning model for image classification.
Technologies & Skills
Use time-series models to predict future stock prices.
Technologies & Skills
Gain hands-on experience from data ingestion to deployed models — the exact skills hiring managers ask for.
Build production-grade ML & DS projects that demonstrate your end-to-end capabilities to employers.
Projects modeled after real business problems used by leading data teams across industries.
Discuss actual implementations in interviews — from feature engineering to model deployment.
Start creating industry-standard Data Science & ML projects today.
Explore diverse career paths after completing the course.
1-3+ Years Experience
Design and implement machine learning models to solve complex business problems.
Salary Range
₹8L - ₹25L+
Essential Skills
Key Responsibilities
Industry Opportunities
Top Hiring Companies
0-2 Years Experience
Analyze large datasets to extract actionable insights and create reports.
Salary Range
₹5L - ₹12L+
Essential Skills
Key Responsibilities
Industry Opportunities
Top Hiring Companies
2-4+ Years Experience
Build and deploy scalable machine learning systems in production.
Salary Range
₹10L - ₹30L+
Essential Skills
Key Responsibilities
Industry Opportunities
Top Hiring Companies
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