Full Stack Data Science Program
This is the most comprehensive Data Science course available, covering all steps of the Data Science process from Data Integration, Data Manipulation, Descriptive Analytics and Visualization to Statistical Analysis, Predictive Analytics and Machine Learning models, using the most in-demand tools like R, Python, SAS, and Tableau. It will enable you to master all three elements of Data Science - Statistics, Tools, and Business Knowledge.
Looking for an in-person, classroom experience? Click here to register for the Data Science Bootcamp 
24 weeks
10 hours / week
12 months
Modules
Data Wrangling and Advanced Manipulation, Statistical Analysis, R for Data Science, Predictive Analytics with R, Machine Learning with Python
Tools
Python, R, SAS, Tableau
MODULES INCLUDED
- An Overview of Analytics and Data Science
- Analytics Methodology and Problem Solving Frameworks
- Models & Algorithms - How they work and Scope
- Using statistics to summarize data effectively
- Visualization methods and applications in Excel
- Building Descriptive Analytics Dashboards
- Case Study - Auto Insurance
- Case Study - Direct Marketing
- R for Data Science - Set Up and Introduction
- Data Import from multiple sources - Flat files, databases, web sources etc
- Basic data manipulation with R - summarizing, aggregating, functions
- Advanced data manipulation with R including custom functions
- Building effective visualizations with R
- Case Study - Credit Card spend patterns
- Case Study - Response Modeling Data
- Exploratory Data Analysis
- Cleaning Data - missing values, outliers
- Preparing Data for Modeling - Transformations, derived variables
- Case Study - Campaign Response models
- Case Study - Second hand car pricing
- Introduction to Inferential Statistics
- Understanding Probability and Distributions
- Sampling theory and how to choose representative samples
- Hypothesis Testing Concepts and Frameworks
- Single sample Hypothesis tests - Z and T
- Two Sample tests - Independent and Paired
- Multiple Samples tests - ANOVA, Chi Square
- Non-parametric tests
- Case Study - HR Analytics
- Case Study - Sales and Marketing effectiveness
- Linear Regression Models - How they work
- The OLS algorithm and implementation in R
- Model building and iterations with Linear Models
- Interpretation of output and evaluating model results
- Generating business insights and outcomes from linear models
- Logistic Regression models and the MLE algorithm
- Understanding the odds ratio
- Building logistic models in R
- Evaluating logistic regression output - probabilities, confusion matrix, concordance, lift
- Generating business insights and outcomes from linear models
- Time Series concepts
- Simple Exponential Smoothing
- Holt-Winter's
- ARIMA
- Case Study - Market Mix Modeling
- Case Study - Default scorecard modeling
- Case Study - Predicting debit card usage
- Understanding the Machine Learning approach to algorithms
- Introduction to Python - Set Up, Libraries
- Introduction to Pandas
- Data Manipulation with Pandas
- Visualization in Python: MatplotLib
- Feature Engineering with Structured and Unstructured Data
- Case Study - Customer Analytics
- Understanding Tree Based Algorithms
- Regression Trees
- Classification Trees
- Decision Trees
- Random Forest and Ensemble Methods
- Bagging and Boosting Algorithms
- K-means Clustering
- Case Study - Store Clustering
- Case Study - Brand Perception for Snack manufacturer
- Case Study - Text analytics with product reviews
- Capstone Project - Building a churn scorecard for telecom
- An Introduction to the SAS language
- Data Import into SAS
- Data Manipulation with SAS
- Advanced Data Manipulation with SAS
- Understanding Visualization and Storytelling Principles
- Information Hierarchy
- The appropriate use of Color
- Building interactive dashboards with Tableau
- Building interactive dashboards with Power Bi
- Creating an effective Story with Data
- Visualisation with Tableau
- SQL and Relational Database 101
- Using R with Databases
- Watson Analytics 101
- 60 different datasets and case studies including
- Insurance Claim analysis
- Campaign Response Modeling
- Promotion and marketing effectiveness
- Credit scorecard building
- HR churn prediction
- Capstone Project - Building a churn scorecard for telecom
LEARN FROM THE EXPERTS
Gaurav Vohra
Gaurav has over 18 years of analytics experience and is a data science and business analytics expert.
S Anand
Kathirmani Sukumar
Kathirmani is a Data Visualization, Machine Learning and IoT expert with over 8 years of analytics experience.
Snehamoy Mukherjee
Snehamoy is a Data Science and Machine Learning expert with over 15 years of analytics experience.
Sarita Digumarti
Sarita is an expert in business analytics training, with over 18 years of experience in analytics and consulting.
Sandhya Kuruganti
Sandhya is a senior analytics leader and author with over 20 years of experience.
Puneet Gambhir
Puneet is an eCommerce and analytics expert with over 10 years of experience including working at Flipkart and Lazada.
career facts
India – INR 6 lakhs to 12 lakhs (entry level)
Global – $65,000 to $130,000
Prepares, manipulates and and analyzes data. Tells stories and provides insights from data to guide business decision.
Lead Data Scientist or Chief Data Scientist
Data Science Project Manager
Retail, eCommerce, Banks, Telecom, FMCG, Manufacturing and other domains where data is generated.
WHAT YOU GET
The Catalyst Approach
Learn through video lectures, live Q&A sessions conducted by the faculty, assignments, interactive case study workshops with senior faculty and industry mentors. Know more.
Jigsaw Learning Center
Gain free access to a variety of resources like handouts, reference material, guides, lecture transcripts and student forums for your course duration
Faculty Assistance
Get all your course-related queries solved by the Jigsaw Faculty via email, phone and chat for your program duration.
General Support
We have your back! Our student support teams are available on the weekends for call and 24/7 on email for your course duration
Q&A Online Sessions
Have questions? Ask our analytics mentors during the 2 hour Q&A session every Saturday for your program duration
Career Counseling
Avail professional guidance on resume building, interview preparation and identification of relevant opportunities, for the analytics field.
Mobile App
Learn on the go, wherever you are with mobile access to Jigsaw's course videos.
Jigsaw Lab
Access to a cloud-based solution, for hands-on experience with real-life business data using the latest analytical tools.
Capstone Project
Hands-on industry project experience
FINAL OUTCOME
After completing this specialization, you would have mastered the most popular analytical tools – SAS, R, Python and Advanced SAS (SQL and Macros) in data science using Tableau. The new and exhaustive data science skill set acquired through this online, data science certification course would enable you to build your analytics career optimally.
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