Data Science course helps you gain expertise in Machine Learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, Naive Bayes using R. You’ll learn the concepts of Statistics, Time Series, Text Mining and an introduction to Deep Learning. You’ll solve real life case studies on Media, Healthcare, Social Media, Aviation, HR.

What are the objectives of this course?

After the completion of the course, you should be able to:

Gain insight into the ‘Roles’ played by a Data Scientist
Analyze several types of data using
Describe the Data Science Life Cycle
Work with different data formats like XML, CSV etc.
Learn tools and techniques for Data Transformation
Discuss Data Mining techniques and their implementation
Analyze data using Machine Learning algorithms in
Explain Time Series and it’s related concepts
Perform Text Mining and Sentimental analyses on text data
Gain insight into Data Visualization and Optimization techniques
Who is it intended for?

The course is designed for all those who want to learn about the life cycle of Data Science, which would include acquisition of data from various sources, data wrangling and data visualization. Applying Machine Learning techniques in R language, and wish to apply these techniques on different types of Data. The following professionals can go for this course:
1. Developers aspiring to be a ‘Data Scientist’
2. Analytics Managers who are leading a team of analysts
3. Business Analysts who want to understand Machine Learning (ML) Techniques
4. Information Architects who want to gain expertise in Predictive Analytics
5. ‘R’ professionals who want to captivate and analyze Big Data
6. Analysts wanting to understand Data Science methodologies

Requirements

There is no specific pre-requisite for the course, however basic understanding of R can be beneficial. MyCareerCube offers you a complimentary self-paced course, i.e. “R Essentials” when you enroll in Data Science Certification Training.