Advanced Data Modeling for Decision Making
Master Feature Engineering to Predictive Analytics and everything in between
3 Weeks Live Sessions | 4th Weekend Campus Immersion
In this bootcamp you will master a practical level understanding of Modeling and Optimization techniques using various Data Science methods. Under the expert guidance of a mentor, you will train in storytelling with data and creating an industry-ready portfolio that can catapult your career into new heights.
Prerequisite: Fair understanding of Statistics and familiarity with Programming in R or Python
Talk to Admissions: 9740-991-601
Why this Bootcamp
Work on Real-life Data Science Problems
Take your career headon by working on projects using a competency based learning paradigm. Quality of time spent and the outcome is far more important than the quantity.
Work 1:1 with a Mentor
We pair you with a mentor who has extensive professional and academic knowledge of the field. You’ll have one-on-one conversations with your mentor, and receive useful feedback on improving your work.
We Will Keep You Engaged
Our mentors are here to keep you motivated, answer questions, provide feedback, and help deepen your understanding of essential tools and techniques. Learn with live online classes and face to face sessions. Learning is best when you are able to ask the questions and clarify your doubts with the faculty.
What You Will Learn
Unit 1: Modeling and Feature Selection
■ Introduction to Modeling in Data Science
■ Feature Selection and Dimensionality Reduction
■ CRISP-DM and Knowledge Discovery
■ Anomaly Detection
Unit 2: Time Series Analysis
■ Time Series Analysis
Unit 3: Optimization
■ Operations Research & Techniques
Unit 4: Text Analytics and NLP
■ Text Analytics, Sentiment Analysis
■ NLP, Social Network Analysis
Unit 5: Visualizing and Presenting your Data
■ Make impactful Data Visualizations
1. Build a model that predicts which patients are likely to be admitted in the hospital within the next one year.
2. Use Anomaly Detection to detect unusual behavior on an endpoint that would indicate malware activity.
3. Build a model to forecast Stock Price Return.
4. Use Social Network Analysis to study the network connections in emails of an organization, to understand who the most connected employees are. This can help in human resource management.
Ability to be learn hands on with real industry data and delivering insights to industry jury is the best part of the program. Data Science and its application for Decision Science with practitioner faculty is the biggest highlight of the program. Strongly Recommend it.