The Data Science and Big Data Analytics course provides practical foundation level training that enables immediate and effective participation in Big Data and other Analytics projects. It includes an introduction to Big Data and the Data Analytics lifecycle to address business challenges that leverage Big Data. The course provides grounding in basic and advanced analytic methods and an introduction to Big Data Analytics technology and tools. Lab sessions offer opportunities to understand how these methods and tools may be applied to real world business challenges by a practicing Data Scientist. This course provides an industry credential for business analysts, data warehouse experts or other professionals with similar backgrounds to help them transform into the world of Data Science and Big Data Analytics that has unprecedented challenges and opportunities.

Topics Covered

R Programming, Basic Differential & Inferential Statistics, Python for Data Science, Fundamentals of Machine Learning, Predictive Modeling, Multiple Supervised & Unsupervised Machine Learning Algorithms with hands on in R & Python, Tableau, Machine learning in Cloud.

Who should attend
This course is intended for individuals seeking to develop an understanding of Data Science from the perspective of a practicing Data Scientist, including; ? Managers of teams of Business Intelligence, Analytics, and Big Data professionals ? Current Business Analysts and Data Analysts looking to add Big Data Analytics skills. ? Database professionals looking to exploit their analytics skills in a Big Data Environment. ? College graduates and graduate students with academic experience in a related discipline looking to move into the world of Data Science and Big Data Analytics.

Pre-requisites
Interest to learn topics on MAths & Statistics

What you need to bring
Laptop"

Key Takeaways
Upon successful completion of this course, participants should be able to; Immediately participate and contribute as a Data Science team member on Big Data Analytics projects by; - Deploying the Data Analytics lifecycle to address Big Data Analytics projects. - Reframing a business challenge as an analytics challenge - Applying appropriate analytic techniques and tools to analyze Big Data, create statistical models, and identify insights that can lead to actionable results - Selecting appropriate data visualizations to clearly communicate analytic insights to business sponsors and analytic audiences Explain how advanced Analytics can be leveraged to create competitive advantage and how the data scientist role and skills differ from those of a traditional business analyst.