Master Data
Become a Data Scientist in 90 days
Master Python, Machine Learning, SQL, Power BI & AI tools with live projects, expert mentors and placement support.
- LEARN FROM THE EXPERTS
- INDUSTRIAL EXPOSURE
- INTERACTIVE CLASSES
- COUNSELOR’S SUPPORT
Students Enrolled
0
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Course Duration
1
months
Modules
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Live Projects
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What you'll be ready for
Every tool in this course is actively used by data teams at top companies
Data Analysis & Insights
Transform raw data into meaningful insights using industry-standard tools and techniques.
Data Visualization
Create interactive dashboards, charts, and reports that communicate data effectively.
Statistical Thinking
Apply statistical methods to identify trends, patterns, and business opportunities.
Data Cleaning & Preparation
Prepare, organize, and transform datasets for accurate analysis and decision-making.
Business Intelligence & Reporting
Generate actionable reports and dashboards to support strategic business decisions.
Real-World Data Projects
Work on practical datasets and build portfolio-ready projects used in industry.
Who This Course is For
Students who have completed 12th and wish to pursue further studies
in Data Science either in India or abroad
Fresh graduates who want to begin their career in Artificial Intelligence
and Data Science.
Professionals seeking growth opportunities in the IT domain.
IT professionals planning to shift their career toward Data Science or
Artificial Intelligence
Developers and Project Managers looking to strengthen their expertise.
Benefits of this Course
Take your e-commerce skills to the next level with our comprehensive Shopify course. This course is designed to guide you step-by-step from setting up your first online store to mastering advanced sales and marketing strategies.Â
In-Demand Skills
Learn the most sought-after data science skills employers need today.
Industry Aligned Curriculum
Master tools and techniques used by leading companies.
Job Ready Training
Build practical expertise to confidently enter the workforce.
Expert Led Sessions
Learn directly from experienced industry professionals.
Hands On Learning
Gain real-world experience through practical exercises and labs.
High Growth Opportunities
Unlock career paths in one of the fastest-growing fields.
Real World Projects
Work on industry-relevant projects to strengthen your portfolio.
Future Proof Skills
Develop skills that remain valuable in an AI-driven future.
Course Curriculam
Module 1 - Introduction to data science and Python Basics
- What is Data Science
- Difference b/w Data Analytics & Science
- Data Science Case Studies
- Setup Jupyter Notebook
- Quick recap of Python syntax
- Variables, data types and operators
- Lists, tuples, dictionaries and sets overview
- Writing simple functions
- Overview of modules and libraries
Module 2 - Numpy and Pandas For Data Science
- NumPy for numerical computations
- Arrays, indexing and vectorized operations
- Pandas DataFrames
- Importing and loading CSV files
- Data manipulation
- Data cleaning
- Grouping, merging and filtering operations
- Real world dataset practice
Project 1 : CSV Data Analyzer
Project 2 : Mini Ecommerce Shop
Module 3 - Data Visualization with Matplotlib and Seaborn
- Importance of data visualization
- Charts in Matplotlib
- Bar, line, pie, histogram, stacked charts
- Seaborn visualizations
- Heatmaps, pairplots, distribution plots
Project 1 : Weather Visualization Dashboard
Project 2 : COVID-19 Data Visualization
Module 4 - EDA & Data Preprocessing
- What is EDA and Need
- Univariate VS Bivariate VS Multivare Analysis
- Understanding the Problem and the Data
- Visulizing Relationship of Data
- Data Wrangling File Handling
- Data Pre Processing
Module 5 - Mathematics for Data Science
- Statistics (Mean, Meadian, Mode, range, variance)
- Probility (Events, Types of Probility ,Baye ' s Theorem)
- Distribution : (Normal, Binomial, z-score)
Module 6 - Machine Learning (Supervised & Unsupervised)
- Understanding Machine Learning Concept
- Simple Linear Regression
- Multiple Linear Regression
- Logistic Regression ML Model
- Decision Tree
- Random Forest
- Boosting Stacking
- Boosting Stacking
- KNN
- Naive Bayes
- Unsupervised ML Clustering
- K-Means
- Hirarchial Clustering
Module 7 - Model Evalution & Tuning
- What is Model Evalution?
- Understanding Model Tuning
- Cross Validation Technique
Module 8 - Time Series Forecasting
- Time Series Concept
- Time Series Visualization Data Preparation
- Time Series Stationarity
- ACF PACF
- ARIMA Model
- SARIMA Model Forecasting
Module 9 - Deep Learning
- Introduction to neural networks
- ANN working
- Understanding tensors
- Working with TensorFlow
- Forward and backward propagation basics
- CNN introduction
- Data augmentation
- Image processing basics
Module 10 - Capstone Project & Deployment
- Cardiac Diagnosis
- Model Deployment