Course Curriculum

Comprehensive Course Curriculum

Our industry-aligned curriculum is designed by experts to help you master the most in-demand Data Science With AI & ML skills and prepare you for a successful career.

Foundations of Data & Python

Master Python, the go-to language for data science. Learn how to write efficient code, automate tasks, and perform basic analysis with built-in libraries. You’ll also develop confidence in handling structured and unstructured datasets.

Gain hands-on experience using tools like Pandas and NumPy to clean, organize, and explore data. This module builds the essential groundwork for all upcoming analytics and ML work.

What you'll learn:

Learn syntax, variables, and modular code.
Handle lists, dictionaries, and loops.
Analyze data and manage projects.

Python Programming Fundamentals

Learn Python programming fundamentals including syntax, variables, operators, and writing modular, readable code, developing the ability to create clean, efficient programs suitable for data analysis and automation tasks. Read More

Opportunities it opens

Data Structures, Functions, and Loop

Work with essential data structures, functions, and loops including lists, dictionaries, and conditional logic to solve real-world problems by writing reusable, optimized code for analytical applications. Read More

Opportunities it opens

Exploratory Data Analysis (EDA)

Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies in datasets, using both visualizations and statistical methods to generate actionable insights for informed decision-making. Read More

Opportunities it opens

Git & GitHub Version Control

Collaborate efficiently using Git version control and GitHub repositories to manage projects, maintain version history, track changes, and coordinate effectively in team environments. Read More

Opportunities it opens

Statistics & SQL for Analytics

Statistical thinking is the backbone of data science. In this module, you’ll learn to summarize, interpret, and draw conclusions from data. You’ll explore descriptive statistics, probability, and hypothesis testing.

At the same time, you’ll learn SQL — the language of databases — and use it to extract insights from large datasets in business scenarios.

What you'll learn:

Learn descriptive, inferential, and probability concepts.
Master joins, aggregates, and database queries.
Apply SQL to generate actionable insights

Descriptive & Inferential Statistics

Apply descriptive and inferential statistics, including mean, variance, confidence intervals, and distributions, to summarize data, interpret results, and support data-driven decision-making in business and research contexts. Read More

Opportunities it opens

Probability & Hypothesis Testing

Understand probability concepts and conduct hypothesis testing using z-tests, t-tests, and p-values, evaluating assumptions rigorously and making statistically sound business or research conclusions. Read More

Opportunities it opens

SQL Joins & Aggregates

Query relational databases using SQL with joins, aggregates, filters, and subqueries to extract insights, building the ability to analyze structured data and solve business problems efficiently. Read More

Opportunities it opens

Business Case Analytics

Apply SQL techniques to real business cases, generating insights from raw transactional and operational data, and translating database queries into meaningful metrics to support strategic decisions. Read More

Opportunities it opens

Machine Learning

Learn the core concepts and algorithms that power recommendation engines, fraud detection, and intelligent decision systems. This module introduces both supervised and unsupervised learning.

You’ll build machine learning models, evaluate performance, and apply them to structured data for predictive analysis.

What you'll learn:

Train models using regression, trees, clustering.
Classify, predict, and assess model performance.
Build and deploy end-to-end solutions.

Supervised & Unsupervised Learning

Train supervised and unsupervised machine learning models including linear regression, decision trees, and clustering to develop predictive and segmentation models addressing real-world analytical challenges. Read More

Opportunities it opens

Classification & Regression

Perform classification and regression tasks to predict categories and continuous values using datasets, learning to select appropriate algorithms and interpret model outcomes effectively. Read More

Opportunities it opens

Model Tuning & Evaluation

Evaluate and tune machine learning models using metrics such as accuracy, F1-score, and precision-recall, developing expertise in optimizing performance and ensuring reliable predictions in practical applications. Read More

Opportunities it opens

ML Project Execution

Design and execute end-to-end machine learning pipelines including preprocessing, modeling, and deployment in Jupyter, gaining hands-on experience delivering complete AI/ML solutions ready for production environments. Read More

Opportunities it opens

Deep Learning & AI

Step into the world of artificial intelligence through hands-on experience with neural networks. Learn how to process visual and textual data and build intelligent systems.

This module includes both theoretical understanding and practical use of popular deep learning frameworks.

What you'll learn:

Build feedforward and deep learning models.
Analyze images and sequential data efficiently.
Process text for sentiment and insights.

Neural Networks with TensorFlow/Keras

Build feedforward neural networks using TensorFlow/Keras for classification tasks across various domains, understanding activation functions, loss optimization, and evaluating model performance for deep learning applications. Read More

Opportunities it opens

CNNs for Image Recognition

Analyze images using convolutional neural networks (CNNs) to classify and extract visual patterns, learning convolution layers, pooling, and activation techniques for image recognition tasks. Read More

Opportunities it opens

RNNs & LSTMs for Time-Series

Handle sequential and time-series data using recurrent neural networks (RNNs) and LSTMs, building predictive models for text, stock prices, and other sequential datasets. Read More

Opportunities it opens

NLP for Text Analysis

Build NLP models to classify sentiment, extract keywords, or summarize textual content, learning to preprocess, vectorize, and model text data for business and AI applications. Read More

Opportunities it opens

BI Tools & Big Data

Learn how to visualize insights, communicate results, and work with high-volume datasets. This module connects your data skills with business decision-making.

Understand how dashboards drive strategic decisions and explore the basics of big data architecture.

What you'll learn:

Build interactive dashboards with Power BI, Tableau.
Aggregate data and track key metrics.
Explore Spark, Hadoop, and real datasets.

Malware Detection with ML

Create interactive dashboards and compelling data stories in Power BI and Tableau for stakeholders, developing skills to visualize, analyze, and communicate business metrics effectively. Read More

Opportunities it opens

Power BI & Tableau

Calculate business metrics, aggregate data, and design KPIs using drill-downs and filters, to monitor performance and present actionable insights for strategic decision-making. Read More

Opportunities it opens

Data Aggregation & KPIs

Understand big data concepts including distributed computing, Hadoop, and PySpark fundamentals, gaining knowledge of processing large datasets efficiently and integrating big data tools into analytics workflows. Read More

Opportunities it opens

Big Data Concepts & Spark

Analyze messy, real-world datasets from sectors like e-commerce and banking to extract insights, applying practical techniques to clean, process, and interpret complex datasets for decision-making. Read More

Opportunities it opens

Real-World Case Studies

Complete a capstone AI/ML project by solving an industry-relevant problem end-to-end, demonstrating skills in development, deployment, and showcasing solutions on GitHub for professional portfolios. Read More

Opportunities it opens

Capstone Project & Career Readiness

Apply everything you’ve learned to build a full-scale AI/ML project. Choose your domain, gather data, model outcomes, and present insights just like in the real world.

You’ll also receive personalized support to polish your profile and prepare for interviews with hiring managers.

What you'll learn:

Solve real-world AI/ML problems end-to-end.
Optimize resume, LinkedIn, and interview skills.
Present projects to mentors and recruiters.

Capstone AI/ML Project

Opportunities it opens

Resume & LinkedIn Optimization

Optimize your resume and LinkedIn profile to position yourself competitively for data science roles, learning to highlight skills, projects, and achievements effectively to attract recruiters. Read More

Opportunities it opens

Mock Interviews & Case Rounds

Practice mock interviews and case rounds with expert mentors covering behavioral and technical questions, building confidence, refining problem-solving approaches, and preparing for real-world hiring scenarios. Read More

Opportunities it opens

Final Demo Day

Present your capstone project during a live demo day to mentors and potential recruiters, gaining experience presenting insights professionally and receiving feedback from industry experts. Read More

Opportunities it opens

Data Scientist with AI & ML

What role does a Data Scientist with AI & ML play?

Data Scientist

Use AI and ML to analyze complex datasets and create intelligent solutions.

ML Engineer

Build, deploy, and monitor machine learning pipelines in production environments.

AI Engineer

Develop smart systems using neural networks, LLMs, and natural language processing.

Data Analyst

Draw business insights using visual dashboards and statistical data analysis.

Data Engineer

Design robust data pipelines and manage cloud data architecture.

BI Developer

Create interactive reports and dashboards to drive business decisions.

Big Data Specialist

Handle massive datasets using Hadoop, Spark, and distributed computing.

AI Researcher

Work on advanced AI models and contribute to innovative research in deep learning.

Proven 85% Placement Success Across Batches

International Placements

Learners placed in top global companies across UAE, UK, Canada, and more.

10+ Batches 500+ Learners

Transformed 5,000+ Careers

Empowering professionals and freshers to level up through skill-based learning.

110+ Batches 5K+ Learners

100+ Hiring Partners

Trusted by industry-leading recruiters and top-tier startups.

110+ Batches 5K+ Learners

Avg. Salary Hike of 70%

Learners have reported significant hikes post program completion.

1000+ Placements

Expert Faculties

Learn from experienced mentors with proven industry expertise

Ranjitha

Expertise:

Data Science & AI Trainer

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Postgraduate in computer science Certified AI & Machine Learning Professional Specialized training in Python, Machine Learning, Deep Learning and Natural Language Processing Proficient in MLPPS, Model Deployment, and Cloud Integration (AWS)

Jeevitha D S

Expertise:

Power BI, Tableau, SQL, Excel

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Jeevitha is a detail-oriented Principal Instructor – Data Science & AI with 5 years of experience delivering hands-on training in Machine Learning, Deep Learning, MLOps, and Generative AI.

Ravi Singh

Expertise:

Deep Learning & Computer Vision

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Arjun is a researcher turned instructor who specializes in computer vision projects such as image recognition and object detection. His sessions are hands-on, blending theory with projects like self-driving car simulations.

Simran Kaur

Expertise:

Business Analytics & Decision Sciences

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Simran has worked with Fortune 500 companies to solve strategic problems using analytics. She teaches statistical modeling, hypothesis testing, and decision-making frameworks with real case studies.

Dr. Vivek Iyer

Expertise:

Natural Language Processing (NLP)

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With a strong research background, Dr. Vivek has published multiple papers in NLP. He mentors learners on text mining, sentiment analysis, and building conversational AI systems.

Meera Joshi

Expertise:

Data Strategy & Analytics Consulting

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Meera brings 12+ years of corporate consulting experience, teaching how to align analytics with business goals. She emphasizes data storytelling and translating insights into executive-level decisions.

Karan Malhotra

Expertise:

Artificial Intelligence & MLOps

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Karan is an AI solutions architect, training students in production-level ML systems. He focuses on deploying, monitoring, and scaling ML models, bridging the gap between ML and DevOps.

Rahul Mehta

Expertise:

Data Visualization & BI Analytics

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Rahul is a certified BI professional with 10 years in analytics consulting. He helps learners convert raw data into actionable dashboards and KPIs, making him a go-to mentor for visualization enthusiasts.

Real-World Industry Projects

Apply Skills in Real-World Industry Projects

Customer Segmentation for Personalized Banking

Use anomaly detection models to identify suspicious user behavior within corporate systems, flagging potential insider threats in real-time. Analyze logins, file access, and system usage patterns.

Tools Used: SQL, Python (Pandas, Scikit-learn), Tableau
Skills: Clustering, EDA, Dashboarding
Sector: BFSI

Demand Forecasting for Online Retail

Analyze historical sales data and build time series models to predict future demand and improve stock planning and logistics.

Tools: Python (Pandas, Prophet), Excel
Skills: Time Series Analysis, Forecasting, Data Cleaning
Sector: Retail / E-commerce

Churn Prediction for Telecom

Develop a classification model to predict which customers are likely to leave the telecom service and implement retention strategies.

Tools: Python (Scikit-learn, XGBoost), Power BI
Skills: Classification, Imbalanced Data Handling, Model Evaluation
Sector: Telecom

Employee Attrition Analysis in HR

Identify key factors influencing employee exits using logistic regression and decision trees to help HR reduce attrition.

Tools: Python (Logistic Regression, DecisionTree), Excel
Skills: Feature Engineering, Regression, Analytics Reporting
Sector: HR Analytics

Real-Time Credit Card Fraud Detection

Use anomaly detection and classification models to identify fraudulent transactions in real time and minimize financial risk.

Tools: Python (Scikit-learn, PyCaret), Streamlit
Skills: Anomaly Detection, Classification, AUC Optimization
Sector: FinTech

Movie Recommendation System

Build a content-based and collaborative filtering model to recommend movies to users based on their preferences and history

Tools: Python (Surprise, Pandas), Streamlit
Skills: Recommendation Systems, Matrix Factorization, Collaborative Filtering
Sector: Media & Entertainment

Customer Sentiment Analysis from Reviews

Extract insights from product reviews using NLP techniques to classify sentiments and guide product and marketing decisions.

Tools: Python (NLTK, TextBlob), Power BI
Skills: Text Preprocessing, Sentiment Analysis, Data Visualization
Sector: E-commerce

Image Classification for Product Tagging

Develop a convolutional neural network to automatically classify product images into categories for inventory tagging.

Tools: Python (TensorFlow, Keras, OpenCV)
Skills: Computer Vision, CNN, Image Augmentation
Sector: Retail / AI Automation

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Full Stack Program

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PG Data Science With AI & ML Program

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Industry-Relevant Curriculum

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1:1 Mentorship

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Capstone Projects

Comprehensive Course Curriculum

Foundations of Data & Python

What you'll learn:

Python Programming Fundamentals

Data Structures, Functions, and Loop

Exploratory Data Analysis (EDA)

Git & GitHub Version Control

Statistics & SQL for Analytics

What you'll learn:

Descriptive & Inferential Statistics

Probability & Hypothesis Testing

SQL Joins & Aggregates

Business Case Analytics

Machine Learning

What you'll learn:

Supervised & Unsupervised Learning

Classification & Regression

Model Tuning & Evaluation

ML Project Execution

Deep Learning & AI

What you'll learn:

Neural Networks with TensorFlow/Keras

CNNs for Image Recognition