Business Data Analytics with R – LVC
- Offered byPreparationInfo
Business Data Analytics with R – LVC at PreparationInfo Overview
Duration | 32 hours |
Total fee | ₹41,145 |
Mode of learning | Online |
Credential | Certificate |
Business Data Analytics with R – LVC at PreparationInfo Highlights
- Earn a certificate after successful completion
Business Data Analytics with R – LVC at PreparationInfo Course details
- Descriptive analytics, which tracks key performance indicators to understand the present state of a business
- Predictive analytics, which analyzes trend data to assess the likelihood of future outcomes
- Prescriptive analytics, which uses past performance to generate recommendations about how to handle similar situations in the future
- Learn the nuances of data collection, data presentation, and model building using real-life data sets
- Learn how to build supervised and unsupervised machine learning models
- Students will be introduced to algorithms to solve classification and segmentation problems
- They will also get introduced to R platform, and different algorithms which can be used in the model building activity
- At the end of the program leaner will develop a clear understanding of the need for business analytics
- They will be able to apply it to solve some interesting problems cutting across various business domains
- This training program focuses on Forecasting, Econometrics and Time Series Analyze and predict future outcomes based on historical patterns
Business Data Analytics with R – LVC at PreparationInfo Curriculum
MODULE 1: INTRODUCTION TO ANALYTICS, DATA & BASIC STATISTICS
Lecture1.1 Analytics v/s Analysis0m
Lecture1.2 Types of Analytics, Business domains within Analytics0m
Lecture1.3 Types of Data Variables & Summarizing Data0m
Lecture1.4 Central Tendency, Symmetry and Skewness0m
Lecture1.5 Random Variables, Probability Distribution, Central Limit Theorem0m
Lecture1.6 Sampling and Statistical inference, Confidence Intervals0m
Lecture1.7 Case Study 1: Banking Sector Credit Card Department
MODULE 2: BASIC STATISTICS & PREDICTIVE MODELING
Lecture2.1 Hypothesis Testing & Analysis of Variance0m
Lecture2.2 Introduction to Tools and Software commonly used in Analytics0m
Lecture2.3 Multivariate Linear Regression Theory0m
Lecture2.4 Multivariate Linear Regression (Using Excel and R)0m
MODULE 3: PREDICTIVE MODELING & FORECASTING
Lecture3.1 Logistic Regression (Using R)0m
Lecture3.2 Case Study 2:Case: Auto Insurance Company, Banking Sector Credit Card Department0m
Lecture3.3 Case Study 3: Auto Insurance Company, Banking Sector Credit Card Department0m
MODULE 4: TIME SERIES MODELING
Lecture4.1 Models of time series : Moving averages & Autoregressive Models0m
Lecture4.2 Model Estimation , Model Validation & Model forecasting
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