This program has been designed to help meet the expand-ing needs for these "Data Scientists" who are skilled in the utilization of a unique blend of Science, Art and Business.
Corporation has dramatically increased investments in their "digital enterprises" in past few years. It has been estimated that by 2020, IT departments will be monitoring 50 times more data than they are today. This tidal wave of data is driving unprecedented demand for those with the skills required to manage and leverage these very large data sets into competitive advantage.
This program has been designed to help meet the expand-ing needs for these "Data Scientists" who are skilled in the utilization of a unique blend of Science, Art and Business. These professionals are skilled in automating methods of collecting and analyzing data and utilizing inquisitive exploring techniques to discover previously hidden insight from this data that can profoundly impact the success of any business.
Academically Rigorous: EduPristine is known for class room training and project-based learning. Data Science Program is no exception. The program is designed and delivered by the experience faculty and data science professionals who teach on the EduPristine campus.
Live Classes: Delivered in a state-of-the-art, datascience@Edupristine blends live, face-to-face classes unlike our other classroom learning experiences, our platform facilitates collaboration, meaningful discussion, and lifelong connections
Individuals with a bachelor's degree in engineering, science, math/statistics, finance, computer science, accounting or marketing who enjoy statistical and analytical, thinking may excel in this field.
Prepare rigorously before competitive exam.
work on real time cases from different domains.
This course serves as an introduction to the interdisciplinary and emerging field of data science. Students will learn to combine tools and techniques from statistics, computer science, data visualization and the social sciences to solve problems using data.
work on real time cases from different domains.
Online Access to Course Material (Unlocked Excel Models, Presentations, etc.)
Download the study notes to supplement subject wise video tutorials & webinar recordings
|Exclusive 4 Day MasterClass|
|Day 1: Introduction to Analytics and Data|| Analytics v/s Analysis
Types of Analytics, Business domains within Analytics
Data Motivation, Completed and Processed Data
Components of Tidy Data
Downloading and Reading Local files, Excel files and XML
Reading from MySQL, The Web, APIs and other sources
Subsetting and sorting Data
Reshaping and Merging Data
Types of Data Variables & Summarizing Data
Case Study 1: Banking Sector Credit Card Department
|Day 2: Basic Statistics and Predictive Modeling|| Central Tendency, Symmetry and Skewness
Random Variables, Probability Distribution, Central Limit Theorem
Sampling and Statistical inference, Confidence Intervals, Hypothesis Testing
Multivariate Linear Regression Theory
|Day 3: Predictive Modeling|| Multivariate Linear Regression (Using Excel and R)
ANOVA, R-Square, p-values, vif, Multicollinearity, Heteroskedasticity, Gini coefficient
Case Study 2: Auto Insurance Company, Banking Sector Credit Card Department
|Day 4: Predictive modeling and Forecasting (Time series Modeling)|| Logistic Regression (Using R): Gini coefficient, vif
Case Study:Credit card, Banking Sector Credit Card Department
Models of time series
• Moving averages
• Autoregressive Models
Case Study 4: Sales Forecasting of Automobile company
It blended with my experience as a controller for a construction company. Specifically integrating the BS, P&L and CFS. I like modeling, budgeting and releasing Pro Forma statements. Aslo, I liked the way dates were used.
I followed the course closely, it was helpful both from the perpective of understanding financial modeling as well as to improve my knowledge of excel. Hoping to master my skills over time with EduPristine's support.
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