Only 5 members are allowed each class.

Topics Covered

Data scientist Course Content: Section-1 1. Introduction To Business Analytics and Business Intelligence 2. Introduction to Data Collection and Data Mining 3. Analytics Methodology and Problem Definition 4. Data Exploration and Data Preparation 5. Introduction to Statistics for Business Analytics 6. Descriptive Statistics in Data Analytics 7. Inferential Statistics and Hypothesis Testing 8. Introduction to Regression and Predictive Modeling 9. Introduction to Analytics in Excel 10. Advanced Analytics in Excel with a Case Study Section – 2 1. Introduction to R 2. R coding Practices and Advantages of R 3. Importing and Exporting Data in R 4. Introduction to Advanced Statistical Methods 5. Non-Parametric Tests 6. Data Transformation and Data manipulation in R 7. Data Exploration in R 8. Linear Regression and Logistic Regression in R 9. Data Visualization in R and Tableau 10. Working with Tableau Section – 3 1. Introduction to Clustering 2. Cluster Profiling 3. K-Means Clustering and Hierarchical Clustering 4. Clustering in R 5. Introduction to Decision trees 6. Creating Decision Trees 7. Using Decision Trees with a Case Study 8. Introduction to Text Mining 9. Text Analysis Process and Sentiment Analysis in R 10. Time series Analysis using R Section – 4: Project on Financial Analytics or Web Analytics or Retail Analytics

Who should attend

Degree and Above students

Pre-requisites

Degree

What you need to bring

Note book

Key Takeaways

Expertise knowledge in Data Scientist and Data Analyst.We offer Job assistance.