Applied Data Science
This course is perfect for participants looking to gain practical analytical and technical skills to solve real-world problems and challenges revolving around data.
By enrolling in this course, participants will develop a deep and profound understanding of Big Data Analytics (BDA) and the Data Science lifecycle, and be able to develop predictive models and recommendation engines. As the course focuses on the application of data science to business processes and operations, participants will be able to pick up skills in capturing, managing, analyzing and decision-making based on data.
This course caters to those with experience in Data Science with intentions of becoming full-fledged Data Scientists. Participants should preferably have some knowledge in Python or R and are recommended to complete the Applied Data Analytics course.
- Data Science Overview
- Data Science Lifecycle
- Data Acquisition & Cleansing
- Data Analysis & Statistical Methods
- Introduction to Machine Learning
- Introduction to Spark & MLlib
- Predictive Modeling (Linear Regression, Clustering, Decision Tree, Random Forests)
- Building a Recommender System
- Model Evaluation
- Creating Simulation Models & What-Ifs
- Natural Language Processing & Sentiment Analysis
- Geo-Clustering Analysis
- Graph Analysis