- Popular
Post Graduate Program in Data Science and A.I.
- 4.5/5 (1500+ Student's Ratings)
Next Cohort
This Week
Duration
12 Months . Online
06 Months
Live Internship
Eligibility
Freshers, Graduates, Experienced
What Our Program Offers?
Our Data Science program equips you with industry-ready skills through advanced tools and expert support.
- 1:1 Doubt Clearing Session
- Live Hackathons
- Lifetime Career Support
- Webinars And Workshops
- Extensive Course Materials
- 250+ Hours of Self Paced Learning
- 400+ Hours of Live classes
- Industry Expert Mentors
- 360° Placement Assistance
- 24/7 Student Support
- Personalized Learning Paths
- Regular Assessments
- Progress Tracking
- Networking Opportunities
- Flexible Learning Schedules
- Strong Alumni Network
- Interview Preparation
- Certification Programs
- Interactive Learning Platform
- Real World Projects
What Sets inGrade Apart?
Industry-Leading Curriculum
Stay ahead with cutting-edge content designed to meet the demands of the tech world.
Expert Instructors
Learn from top professionals who bring real-world experience to every lesson.
Hands-on learning
Master skills with immersive, practical projects that build confidence and competence.
Placement-Oriented Sessions
Jump-start your career with results-oriented sessions guaranteed to get you the best jobs
Flexible Learning Options
Learn on your schedule with flexible, personalized learning paths.
Lifetime Access to Resources
You get unlimited access to a rich library of materials even after completing your course.
Community and Networking
Connect to a global community of learners and industry leaders for continued support and networking.
High-Quality Projects
Build a portfolio of impactful projects that showcase your skills to employers.
Freelance Work Training
Gain the skills and knowledge needed to succeed as freelancers.
Course Curriculum
This course will equip you with basics of data science skills such as statistics essentials, mathematics. You will learn concept such as skewness, correlation, regression, and distribution, eigenvalues and eigenvector. Programming skills such as data types, variables, strings, loops, and functions such as multithreading and multitasking using Python, Pivots, and lookups in Excel and SQL
- Modules
Excel for Data Analytics
Excel Essentials & Core Functions
- Understand cell referencing and core formulas
- Format data, handle dates/text, and use shortcuts
- Learn basic data validation and error handling
Logic, Lookup & Data Cleaning
- Master IF, AND, OR, VLOOKUP, INDEX-MATCH, XLOOKUP
- Clean data using Power Query tools and conditional formatting
- Handle duplicates, missing data, and errors effectively
Pivot Tables & Advanced Power Query Scenario Management.
- Build pivot tables, slicers, and perform drill-downs
- Use Power Query for joins, grouping, unpivoting
- Automate parameter-based transformations
Dashboards, Reporting & What-If Analysis and Forecasting.
- Create interactive dashboards with charts and slicers
- Use Goal Seek, Solver, and Scenario Manager
- Build basic forecasts and protected dynamic reports
Power BI for Business Intelligence
Data Loading, Transformation & Modeling (Power Query + DAX Basics)
- Connect and transform data in Power Query
- Understand relationships, star schema, and calendar tables
- Write DAX formulas, use Time Intelligence functions
Data Visualization, Interactivity & Cloud Publishing
- Build interactive reports with filters, tooltips, bookmarks
- Design best-practice layouts and dashboards
- Publish to Power BI Service and schedule data refresh
Tableau Data Visualization
Tableau Foundations & Interface Mastery
- Learn Tableau’s UI, dimensions vs measures, and basic charts
- Work with filters, aliases, hierarchies
- Connect data and understand metadata
Interactivity, Dashboards & Maps
- Create dynamic dashboards and maps with actions
- Use parameters, sets, calculated fields
- Export visuals and design with best practices
Advanced SQL Techniques
SQL Foundations & Basic Data Manipulation
- Learn core SQL syntax (SELECT, INSERT, UPDATE, DELETE)
- Understand data types, NULL, and RDBMS concepts
- Perform basic queries and aggregations
Filtering, Aggregations & Joins
- Use GROUP BY, HAVING, and multi-table joins
- Apply filtering, subqueries, and aliases
- Write nested queries for advanced reports
Filtering, Aggregations & Joins
- Use GROUP BY, HAVING, and multi-table joins
- Apply filtering, subqueries, and aliases
- Write nested queries for advanced reports
Data Modeling, SQL in Python & Optimization Essentials
- Normalize schemas, use views/indexes
- Integrate SQL in Python using sqlite3/pandas
- Understand JSON, triggers, and stored procedures
Statistics & Hypothesis Testing (Theory)
Statistical Thinking & Descriptive Analytics
- Analyze central tendency, dispersion, and distributions
- Use histograms, boxplots, and scatterplots
- Detect outliers and standardize data
Sampling, Probability & Inferential Statistics
- Apply sampling techniques and CLT
- Understand distributions and conditional probability
- Build confidence intervals and calculate margins of error
Hypothesis Testing & Business Decision-Making
- Perform T-Tests, Z-Tests, Chi-Square, and ANOVA
- Design A/B tests and interpret p-values
- Avoid common errors (Type I/II)
Python Programming
Python Essentials & Core Logic
- Learn syntax, variables, data types
- Use conditionals and boolean logic
- Work with lists, sets, dictionaries
Functions, Comprehensions & Object-Oriented Design
- Write functions, lambdas, and list comprehensions
- Handle files and exceptions
- Understand OOP: classes, inheritance
File Handling, OOPs & External Integration
- Automate file exports (CSV, Excel)
- Parse JSON/APIs and use functional tools
- Apply object-oriented design in scripts
Data Understanding
Data Wrangling with Pandas & NumPy
- Use NumPy arrays and Pandas DataFrames
- Filter, group, merge, and join datasets
- Create pivot tables and aggregations
Data Cleaning, Feature Formatting & Date Handling
- Handle missing data and format strings
- Parse and filter datetime values
- Optimize memory and export clean data
Data Profiling, EDA & Visualization Basics
- Conduct EDA and use profiling tools
- Plot data using Matplotlib and Seaborn
- Customize and export visual reports
Machine Learning
Regression Algorithms & Evaluation
- Build linear/polynomial models
- Train-test split and preprocessing
- Evaluate with MAE, RMSE, R²
Classification Techniques
- Train Logistic Regression, KNN, SVM, Naive Bayes
- Use Decision Trees and Random Forests
- Evaluate using confusion matrix and F1
Model Validation & Optimization
- Prevent overfitting with cross-validation
- Tune models with GridSearch
- Use ROC-AUC for classification performance
Clustering & Association
- Apply K-Means, DBSCAN, Hierarchical clustering
- Discover patterns using Apriori rules
- Analyze results using Support, Confidence, Lift
Text & Image Data Basics (NLP + CV)
- Process text using tokenization, TF-IDF
- Perform sentiment analysis
- Preprocess and classify images
Time Series & Recommender Systems
Time Series Fundamentals
- Analyze trends, seasonality, stationarity
- Use ACF/PACF and ARIMA
- Forecast business metrics
Recommender Systems
- Build collaborative and content-based recommenders
- Apply SVD, NMF for matrix factorization
- Measure performance with MAP, Recall
NLP & Generative AI (Basics)
NLP Fundamentals
- Clean and vectorize text using TF-IDF, Word2Vec
- Run sentiment and NER tasks
- Use Bag-of-Words and embeddings
NLP Applications & Transformers (Intro)
- Understand BERT and Hugging Face APIs
- Perform classification and summarization
- Use GPT models for generation
Generative AI Basics
- Explore GenAI use cases and ethics
- Practice prompt engineering with ChatGPT
- Integrate OpenAI API
Deep Learning
Introduction to Deep Learning & Neural Networks
- Understand MLPs, activation/loss functions
- Learn backpropagation and model architecture
- Use ReLU, Cross-Entropy, Sigmoid
Building Neural Networks with TensorFlow/Keras
- Build models using Sequential API
- Train with optimizers, callbacks
- Prevent overfitting with dropout and early stopping
Image Classification (CNN Basics)
- Create CNN models with Conv/Pooling layers
- Visualize layers and feature maps
- Train on datasets like MNIST
Computer Vision
Computer Vision with OpenCV & Pretrained Models
- Detect objects and edges with OpenCV
- Use models like ResNet/VGG
- Augment and classify images
Custom CV Projects & Real-time Processing
- Build real-time video-based apps (face/emotion detection)
- Deploy CV in basic web interfaces
- Optimize performance and UX
Model Deployment
Model Saving & Serialization
- Save pipelines using Pickle/Joblib
- Export TensorFlow models
- Reuse models in production
Building APIs for ML Models (Flask/FastAPI)
- Create REST APIs with Flask/FastAPI
- Integrate models into endpoints
- Test with Postman
Deploying Models to Cloud
- Host models on Heroku/Render
- Set up logs and autoscaling
- Monitor health of apps
CI/CD and Monitoring
- Build auto-deploy pipelines with GitHub Actions
- Monitor models using MLflow
- Detect model drift and retrain
Transfer Learning
Transfer Learning Concepts
- Fine-tune VGG, ResNet, MobileNet
- Use pretrained models for image tasks
- Apply feature extraction techniques
Hands-on Project & Evaluation
- Apply transfer learning to real data Tune hyperparameters
- Tune hyperparameters
- Evaluate and visualize performance
Intro to Reinforcement Learning
RL Foundations
- Understand agent-environment interaction
- Apply Q-learning and rewards
- Explore exploration vs exploitation
RL Applications & Tools
- Use OpenAI Gym for simulations
- Build basic RL models (CartPole, Grid World)
- Link to real-world cases (games, robotics)
- Internship Program
- Web Scraping from different websites
- Movement Detection with Computer vision
- Model Deployment in Cloud Services
- Data cleaning with Excel and Python
- Data Visualization with Power BI and Tableau
- Model Accuracy Optimization
- Smart Product Recommendations
- Voice Command NLP Models
- Autonomous Deep Learning Solutions
- ML Database Integration
- Soft Skills Program
- Resume Building
- Communication Skills
- Interview Preparation
- Time Management
- HR Round Guidance
- E-mail Writing
- Personality Development
- Emotional Intelligence
- Conflict Management
- Salary Negotiation
- Creativity
- Get Certification
Post Graduate Program in Data Science and A.I.
12 months . Online-
100% Secure Transactions
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Multiple Payment Options
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24/7 Payment Support
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EMI Option Available
Languages and Tools Covered
Projects
Predictive Maintenance
AI analyzes sensor data to predict machinery failures, reducing downtime and ensuring smooth operations in manufacturing, power plants, and transportation.
Skills Needed →
Fraud Detection
Financial institutions use AI to detect fraudulent patterns in transactions, ensuring consumer protection and system integrity.
Skills Needed →
Personalized Medicine
Data science helps analyze medical and genetic data to predict disease risks and create tailored treatment plans for better healthcare outcomes.
Skills Needed →
Customer Churn Prediction
Businesses use data science to identify customers likely to leave, enabling proactive retention strategies through targeted marketing and improved services.
Skills Needed →
Climate Change Analysis
Data science helps analyze climate data to model weather patterns, assess climate risks, and guide policy decisions to address environmental challenges.
Skills Needed →
Stock Market Prediction
AI and data science are used to analyze market trends and historical data, helping investors make informed financial decisions.
Skills Needed →
Self-Driving Cars
Data science helps analyze medical and genetic data to predict disease risks and create tailored treatment plans for better healthcare outcomes.
Skills Needed →
Recommender Systems
Recommender systems analyze user data to suggest personalized products or content, improving user experience on platforms like streaming and shopping sites.
Skills Needed →
Case Studies
Hiring Partners
Meet our inGraders
Application Process for inGrade
Career Consultation
Assess eligibility with our Career Counsellor.
Personalized Guidance
Receive an acceptance letter if eligible.
Easy Registration
Pay the booking amount to confirm your seat.
Start Upskilling
Access the curriculum and begin your journey.
Ongoing Support
Receive continuous mentorship and career assistance.
Live Interactive Sessions
Join instructor-led live sessions where you can ask questions, join discussions, and engage with peers. The live sessions will help deepen your understanding while keeping you connected throughout the program.
Live Interactive Sessions
Join instructor-led live sessions where you can ask questions, join discussions, and engage with peers. The live sessions will help deepen your understanding while keeping you connected throughout the program.
Self-Paced Learning Content
Start your learning journey with our comprehensive self-paced modules. Access video lessons, reading materials, and exercises that fit your schedule, allowing you to learn at your own pace and revisit topics whenever needed.
Regular Evaluations
Track your progress with regular assessments. Through quizzes, assignments, and hands-on projects, you’ll continually measure your understanding and improve your skills, ensuring you stay on course.
Regular Evaluations
Track your progress with regular assessments. Through quizzes, assignments, and hands-on projects, you’ll continually measure your understanding and improve your skills, ensuring you stay on course.
Personalized Doubt Sessions
If you need extra help, our experts are available for personalized, one-on-one doubt clearing sessions. Get the support you need to tackle challenging topics at any time confidently.
Hands-On Projects & Case Studies
Work on practical, real-world projects and case studies simulating real-world industry challenges. You apply what you have learned by hands-on approach while enhancing your ability to think critically and creating a portfolio you can take to employers.
Hands-On Projects & Case Studies
Work on practical, real-world projects and case studies simulating real-world industry challenges. You apply what you have learned by hands-on approach while enhancing your ability to think critically and creating a portfolio you can take to employers.
Focused Learning Tracks
Choose specific learning tracks, which focus on specialized learning tracks, including machine learning, data visualization, or artificial intelligence, focusing on what really interests you most and where it would take you towards achieving your career goals.
Industry-Specific Expertise
Get in-depth knowledge in your desired field, whether it’s healthcare, finance, or e-commerce. This specialized expertise will help you stand out and make you more competitive in your industry of interest.
Industry-Specific Expertise
Get in-depth knowledge in your desired field, whether it’s healthcare, finance, or e-commerce. This specialized expertise will help you stand out and make you more competitive in your industry of interest.
Interview Preparation
Be prepared to succeed with comprehensive interview coaching that covers technical, behavioral, and case study questions. Our support extends to career counseling, including resume reviews, job search strategies, mock interviews, LinkedIn optimization, and much more.
Alumni Highlights
-
400+
Global Companies -
6 LPA
Average CTC -
34.7 LPA
Highest CTC -
84%
Average Hike
Learning is better with Ingrade
- Launch your career in Data Science today
- Earn up to ₹ 40 LPA at leading companies
- For college students, graduates & working professionals
👋 Connect with our Experts for Counselling Session
Frequently Asked Questions
What is the difference between Data Science and AI?
Data Science extracts insights from data, while AI uses those insights to make machines intelligent..
Do I need a background in programming to start a Data Science and AI course at InGrade?
While it’s helpful, InGrade offers beginner modules to get you up to speed on necessary programming skills.
Which programming languages are essential for Data Science and AI at InGrade?
Python and R are the most commonly used languages, with Python being particularly popular in AI.
What are the prerequisites for enrolling in a Data Science and AI course at InGrade?
Basic knowledge of mathematics, statistics, and some programming experience is beneficial, but not mandatory.
What kind of projects will I work on during the InGrade course?
Projects include real-world data analysis, machine learning model development, data visualization, and AI system implementation.
How long does it take to complete a Data Science and AI course at InGrade?
It depends on the program, but typically it ranges from a few months to a year.
Will I receive a certification upon completion from InGrade?
Yes, InGrade provides a certification upon successful completion of the course.
Can I take InGrade's course online?
Yes, InGrade offers flexible online versions of their Data Science and AI courses.
What is the job market like for Data Science and AI professionals?
The demand for skilled Data Science and AI professionals is high, with competitive salaries and opportunities across various industries.
What kind of support is available during the InGrade course?
Support includes 1:1 doubt clearing sessions, mentorship, forums, and live chat assistance.
