What are the learning objectives?

Simplilearn's Data Scientist Master’s Program will help you master skills and tools like Statistics, Hypothesis testing, Clustering, Decision trees, Linear and Logistic regression, R Studio, Data Visualization, Regression models, Hadoop, Spark, PROC SQL, SAS Macros, Statistical procedures,Advanced analytics, Matplotlib, Excel analytics functions, Hypothesis testing, Zookeeper, Kafka interfaces. These skills will help you prepare for the role of a Data Scientist.

The program provides access to high-quality eLearning content, simulation exams, a community moderated by experts, and other resources that ensure you follow the optimal path to your dream role of data scientist.

Why be a Data Scientist?

A data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data scientist, you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.

What projects are included in this program?

This Data Scientist Master's program includes 10+ real-life, industry-based projects on different domains to help you master concepts of Data Science and Big Data. A few of the projects, that you will be working on are mentioned below:

Project 1: Learn how leading Healthcare industry leaders make use of Data Science to leverage their business.

Domain: Health Care

Description: Predictive analytics can be used in healthcare to mediate hospital readmissions. In healthcare and other industries, predictors are most useful when they can be transferred into action. But historical and real-time data alone are worthless without intervention. More importantly, to judge the efficiency and value of forecasting a trend and ultimately changing behavior, both the predictor and the intervention must be integrated back into the same system and workflow where the trend originally occurred.

Project 2: Understand how the Insurance leaders like Berkshire Hathaway, AIG, AXA, etc make use of Data Science by working on a real-life project based on Insurance.

Domain: Insurance

Description: Use of predictive analytics has increased greatly in insurance businesses, especially for the biggest companies, according to the 2013 Insurance Predictive Modeling Survey. While the survey showed an increase in predictive modeling throughout the industry, all respondents from companies that write over $1 billion in personal insurance employ predictive modeling, compared to 69% of companies with less than that amount of premium.

Project 3: See how banks like Citigroup, Bank of America, ICICI, HDFC make use of Data Science to stay ahead of the competition.

Domain: Banking

Description: A Portuguese banking institution ran a marketing campaign to convince potential customers to invest in a bank term deposit. Their marketing campaigns were conducted through phone calls, and sometimes the same customer was contacted more than once. Your job is to analyze the data collected from the marketing campaign.

Project 4: Learn how Stock Markets like NASDAQ, NSE, BSE, leverage on Data Science and Analytics to arrive at a consumable data from complex datasets.

Domain: Stock Market

Description: As a part of the project, you need to import data using Yahoo data reader of the following companies: Yahoo, Apple, Amazon, Microsoft, and Google. Perform fundamental analytics including plotting closing price, plotting stock trade by volume, performing daily return analysis, and using pair plot to show the correlation between all the stocks.

Project 5: See how Data Science is used in the field of engineering by taking up this case study of MovieLens Dataset Analysis.

Domain: Engineering

Description: The GroupLens Research Project is a research group in the Department of Computer Science and Engineering at the University of Minnesota. The researchers of this group are involved in many research projects related to the fields of information filtering, collaborative filtering, and recommender systems.

Project 6: Understand how leading retail companies like Walmart, Amazon, Target, etc make use of Data Science to analyze and optimize their product placements and inventory.

Domain: Retail

Description: Analytics is used in optimizing product placements on shelves or optimization of inventory to be kept in the warehouses using industry examples. Through this project, participants learn the daily cycle of product optimization from the shelves to the warehouse. This gives them insights into regular occurrences in the retail sector.

What type of jobs are ideal for data science-trained professionals?

Jobs that are ideal for data science-trained professionals include:

  • Statistical programming specialist
  • Data analyst
  • Data scientist
  • Data science manager

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Last updated October 21, 2018
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