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PG Diploma in Data Science
Master the entire toolbox you need to become a data scientist . Utilize our tested and practical techniques for data analysis in various domains and watch your career grow! No Coding Experience Required .
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Enquire Now
Program Highlights
- 300+ hours of Live Interactive Sessions
- Learn Essential Stats, Maths by Highly Qualified and Experienced Faculty
- 10+ Case Studies
- Internship Opportunities
- Industry-Relevant Curriculum
- Professionally Designed for both Fresher’s and Working Professionals
- Capstone Projects
- Master Class from an Industry Expert
- Build Network with Domain Expert
Why Data Science ?
Data science has emerged as an attractive career option for freshers as well as experienced professionals. The demand for data engineers is very high in sectors like information technology, telecom, manufacturing, finance and insurance, retail and many more.
It is most demanded job in 2021. Big Data Engineers, Machine Learning Engineers, and Data Scientists are the top three emerging jobs on LinkedIn.
As predicted, by 2026 data science and analytics would be having more than 11 million jobs.
India is the second prominent hub of jobs for data scientists.
Ever since 2012, the job positions for Data Scientists have increased by over 650%
Who Can Join?
Certification
Curriculum
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Python Programming
40 Hours
40 Hours
- Download and Install Anaconda Navigator, Different IDE's of Python, Introduction to Jupyter Notebook
- Basic Python Programming (Syntax, Comments, Variables, Data types, Operations)
- Data Structures (List, Dictionary, Set, Tuple and operations)
- Loos and statements (if else, for, while, continue, break)
- In built functions, User defined functions, Lambda function
- Handling date time data
- Exceptions handling
- Introduction to Advanced Python Programming
- Some useful libraries/packages: Numpy, Pandas
Essential Math16 Hours
16 Hours
- Matrix Algebra
- Types of matrices
- Algebraic Operations on matrices
- Transpose, Determinant, Inverse of matrix
- Solving System of Linear Equations
- Eigen values Eigen vectors
- G inverse
- Singular Value Decomposition
- Applications of Matrix algebra in Business cases
- Calculus
- Mathematical Functions
- Derivatives
- Integration
- Gradient Descent Algorithm
- Applications of Calculus algebra in Business cases
Essential Statistics30 Hours
30 Hours
- Introduction, Types of data, Visualizing different types of data, Summarise different types of data
- Random variable, Probability and Probability distributions
- Bernoulli, Binomial, Poisson distribution
- Normal distribution
- Population and Sample
- Sampling Distributions
- Tests of hypothesis (t test, Chi square test, F test for mean, variance, proportion, attribute dependency)
- Correlation and Simple Linear Regression
Data Visualization10 hrs
10 hrs
- Data Visualization Libraries in Python
- Pandas, Matplotlib, Seanborn
- Data Visualization for different types of data
- Bar chart, Pie chart, Histogram, Density plot, scatter plot, scatter matrix
R Programming30 hrs
30 hrs
- Download and Install R, R studio
- Basic R Programming (Syntax, Comments, Variables, Data types, Operations)
- Data Structures in R
- Loos and statements (if else, for, while, continue, break)
- In built functions, User defined functions
- Handling date time data
- Handling text data
- Statistics and Data Visualization in R
Feature Engineering, Dimension Reduction12 hrs
12 hrs
- Transformations on data depending on it’s type
- Min max, Binary, Discretise, Standardize, Log and Power transformations, One hot encoding, Zero One.
- Principle Component Analysis
- Singular Value Decomposition
- Different ways to identify important columns and removing irrelevant columns
Machine Learning44 hrs
44 hrs
- Basics of Machine Learning, Types of Machine learning, Regression, Classification, Model building techniques, Model evaluation techniques
- Supervised Learning: Multiple Linear Regression, Logistic Regression, Naïve Bayes Classifier, K Nearest Neighbour, Decision Tree, Bagging, Random Forest, Boosting, Support Vector Machine, Artificial Neural Network, Deep Learning
- Unsupervised Learning: principle Component Analysis, K means Clustering, Hierarchical Clustering
- Transfer Learning, Model Deployment Basics
- Real Life Applications
Domain Analytics in Health care 10 hrs
10 hrs
- Data Warehousing
- Data Mining
- Data Visualization in Health care
- Data Sets from Industry
- Application of data science in the Health care
Domain Analytics in Finance 10 hrs
10 hrs
- Data Warehousing
- Data Mining
- Data Visualization in Finance
- Data Sets from Industry
- Application of Data Science in Finance
Domain Analytics in E-commerce 10 hrs
10 hrs
- Data Warehousing
- Data Mining
- Data Visualization in E-commerce
- Data Sets from Industry
- Application of Data Science in the E-commerce
Domain Analytics in Digital Media 10 hrs
10 hrs
- Data Warehousing
- Data Mining
- Data Visualization in Digital media
- Data Sets from Industry
- Application of Data Science in Digital Media
Syllabus40 hrs
40 hrs
Domain Analytics in Health care - 10 hours
- Data Warehousing
- Data Mining
- Data Visualization in Health care
- Data Sets from Industry
- Application of data science in the Health care
- Data Warehousing
- Data Mining
- Data Visualization in Finance
- Data Sets from Industry
- Application of Data Science in Finance
- Data Warehousing
- Data Mining
- Data Visualization in E-commerce
- Data Sets from Industry
- Application of Data Science in the E-commerce
- Data Warehousing
- Data Mining
- Data Visualization in Digital media
- Data Sets from Industry
- Application of Data Science in Digital Media
Tableau20 hrs
20 hrs
- Data Visualization
- Working with data
- Working With Filters
- Parameters
- Graphs And Charts
- Stories and dashboards
- Integration with R
My SQL30 hrs
30 hrs
- Introduction
- Features and Benefits of MySQL
- Install and Start MySQL
- Database Basics
- SQL Language and MySQL
- Database Design
- Database Modeling
- Keys
- Normalizatio
- Data Types
- What is NULL?
- Viewing Database Structure
- Database Creation
- Create a New Database Structure
- Creating a Database
- Creating a Table
- Basic Queries
- The SELECT Command
- MySQL Query Browser
- Troubleshooting
- Database Maintenance
- Delete an Entire Database
- Maintaining Tables
- Maintaining Columns
- Indexes and Constraints
- Data Manipulation
- Delete/Modify Table row Data
- The INSERT Command
- The REPLACE Command
- The UPDATE Statement
- The DELETE Command
- Functions
- Simple Functions
- Grouping With Functions
- Joining Tables
- Combining Multiple Tables
- Inner Joins
- Outer Joins
- Exporting/Importing Data
- Exporting Data
- Importing Data
- Sub queries
- What is a Sub query?
- Categories of Sub queries
- Sub query Types
- Placing Sub queries
- Other Sub query Uses
- Other Sub query Uses
- Supplementary Information
- Creating VIEWs
- Transactions
- Storage Engines
- Retrieving Metadata
Program Deliverables
- Programming
- Statistical Data Analysis
- Machine Learning
- Artificial Intelligence
- Tableau
- MY SQL
- Build a Predictive model using ML techniques for important business problems
- Data Warehousing
- Excel
- Data Science Application (Domain-Wise)
Tools and Techniques, you will master
Salary Trends
Career Opportunities
(Industry Wise)
Faculty Profile
Qualified and experienced faculty in their respective areas.
Dr. Sachin Adnaik
Senior Data Scientist
- Ph.D. in Statistics
- 10 years of training experience
- 8 years of experience in Data Analytics
- 8 years of experience in Machine Learning
- Experienced in handling/working with image, genetics and text data
Mr. Atul Phad
Head of Technology,JARS Online Retail Solutions Pvt Ltd
- BE (Computer) with 9 + years of work experience
- Amazon Web Service Solution Architect
- Micosoft Technology Associate-SQL
- Microsoft Azure Certified
- Expert in Tableau, Apache, Hadoop, ETL, Python, Flutter etc
Mr. Rohit Agrawal
Data Base Administrator
- Oracle Certified Database Administrator
- Expert in Python, Big-Data, MongoDB
- Corporate Trainer
