Name: Data Scientist
Item: Data Scientist
Rating: 5

Question 1

About the Data Scientist Master's program developed in collaboration with IBM

Accepted Answer

IBM is the second-largest Predictive Analytics and Machine Learning solutions provider globally (source: The Forrester Wave report, September 2018). A joint partnership with Simplilearn and IBM introduces students to integrated blended learning, making them experts in Artificial Intelligence and Data Science. The Data Science course in collaboration with IBM will make students industry-ready for Artificial Intelligence and Data Science job roles.

IBM is a leading cognitive solutions and cloud platform company, headquartered in Armonk, New York, offering a plethora of technology and consulting services. Each year, IBM invests $6 billion in research and development and has achieved five Nobel prizes, nine US National Medals of Technology, five US National Medals of Science, six Turing Awards, and 10 Inductions in the US Inventors Hall of Fame.

What can I expect from these Data Science courses developed in collaboration with IBM?

Upon completion of this Data Scientist online Master's program, you will receive the certificates from IBM(for IBM courses) and Simplilearn for the courses in the learning path. These certificates will testify to your skills as an expert in Data Science. You will also receive the following:

Access to IBM Cloud Lite account
Industry-recognized Data Scientist Master's certificate

Question 2

What are the learning objectives?

Accepted Answer

Data Scientist is one of the hottest professions. IBM predicts the demand for Data Scientists will rise by 28% by 2020. Data Scientist Master’s program co-developed with IBM encourages you to master skills including statistics, hypothesis testing, data mining, clustering, decision trees, linear and logistic regression, data wrangling, data visualization, regression models, Hadoop, Spark, PROC SQL, SAS Macros, recommendation engine, supervised, and unsupervised learning and more.

This Data Scientist Master’s program covers extensive Data Science training, combining online instructor-led classes and self-paced learning co-developed with IBM. The program concludes with a capstone project designed to reinforce the learning by building a real industry product encompassing all the key aspects learned throughout the program. The skills focused on in this program will help prepare you for the role of a Data Scientist.

Question 3

Why be a Data Scientist?

Accepted Answer

A Data scientist is the top ranking professional in any analytics organization. Glassdoor ranks Data Scientists first in the 25 Best Jobs for 2019. In today’s market, Data Scientists are scarce and in demand. As a Data Scientist, you are required to understand the business problem, design a data analysis strategy, collect and format the required data, apply algorithms or techniques using the correct tools, and make recommendations backed by data.

Question 4

What important Data Science skills you will learn with this Master’s program?

Accepted Answer

Gain an in-depth understanding of data structure and data manipulation
Understand and use linear and non-linear regression models and classification techniques for data analysis
Obtain an in-depth understanding of supervised and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline
Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO, and Weave
Gain expertise in mathematical computing using the NumPy and Scikit-Learn packages
Understand the different components of the Hadoop ecosystem
Learn to work with HBase, its architecture, and data storage, learning the difference between HBase and RDBMS, and use Hive and Impala for partitioning
Understand MapReduce and its characteristics, plus learn how to ingest data using Sqoop and Flume
Master the concepts of recommendation engine and time series modeling and gain practical mastery over principles, algorithms, and applications of machine learning
Learn to analyze data using Tableau and become proficient in building interactive dashboards

Question 5

What Data Science projects are included in this Master's program?

Accepted Answer

This Data Scientist Master's program includes 15+ 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:

Capstone Project:

Description: You will go through dedicated mentor classes in order to create a high-quality industry project, solving a real-world problem leveraging the skills and technologies learned throughout the program. The capstone project will cover all the key aspects of data extraction, cleaning, and visualization to model building and tuning. You also get the option of choosing the domain/industry dataset you want to work on from the options available.
After successful submission of the project, you will be awarded a capstone certificate that can be showcased to potential employers as a testament to your learning.

Project 1: Products rating prediction for Amazon

Domain: E-commerce

Amazon, one of the leading US-based e-commerce companies, recommends products within the same category to customers based on their activity and reviews on other similar products. Amazon would like to improve this recommendation engine by predicting ratings for the non-rated products and add them to recommendations accordingly.

Project 2: Improving customer experience for Comcast

Domain: Telecom

Description: Comcast, one of the leading US-based global telecommunication companies wants to improve customer experience by identifying and acting on problem areas that lower customer satisfaction if any. The company is also looking for key recommendations that can be implemented to deliver the best customer experience.

Project 3: Attrition Analysis for IBM

Domain: Workforce Analytics

Description: IBM, one of the leading US-based IT companies, would like to identify the factors that influence the attrition of employees. Based on the parameters identified, the company would also like to build a logistics regression model that can help predict if an employee will churn or not.

Project 4: Predict accurate sales for 45 stores of Walmart, one of the leading US-based leading retail stores, considering the impact of promotional markdown events. Check if macroeconomic factors like CPI, unemployment rate, etc. have an impact on sales.

Domain: Retail

Description: Walmart runs several promotional markdown events throughout the year. The markdowns precede prominent holidays, such as the Super Bowl, Labour Day, Thanksgiving, and Christmas. The weeks including these holidays are weighted five times higher in valuation than non-holiday weeks. The business is facing a challenge due to unforeseen demand, resulting in stocks running out at times due to inaccurate demand estimation. The macroeconomic factors like CPI, Unemployment Index, etc. also play an important role in predicting the demand, but the business hasn’t been able to leverage these factors yet. As a part of this project, create a model to highlight the effects of markdowns on holiday weeks.

Project 5: Learn how leading Healthcare industry leaders make use of Data Science to leverage their business.

Domain: HealthCare

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 brought into action. However, 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 6: Understand how 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: The 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 the 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 7: See how banks like Citigroup, Bank of America, ICICI, HDFC, etc. 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. Its 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 8: Learn how Stock Markets, such as NASDAQ, NSE, and BSE leverage Data Science and Analytics to arrive at consumable data from complex datasets.

Domain: Stock Market

Description: 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 9: 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 10: 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.

Question 6

Who should take this Data Scientist Master’s program?

Accepted Answer

The Data Science role requires an amalgam of experience, data science knowledge, and correct tools and technologies. It is a solid career choice for both new and experienced professionals. Aspiring professionals of any educational background with an analytical frame of mind are most suited to pursue the Data Science course, including:

IT Professionals
Analytics Managers
Business Analysts
Banking and Finance Professionals
Marketing Managers
Supply Chain Network Managers
Beginners or Recent Graduates in Bachelors or Master’s Degree

Question 7

What are the prerequisites for this Data Science training?

Accepted Answer

Professionals wishing to succeed in this Data Science course should have:

Basic knowledge of statistics
Basic understanding of any programming language

Question 8

What type of jobs will I be suited for after completing this Data Science course?

Accepted Answer

Data Science course, you will have the skills that will help you land your dream job in Data Science. Jobs that are ideal for data science-trained professionals include:

Data Analyst
Data Scientist
Analytics Manager/Lead
Machine Learning Engineer
Statistical Programming Specialist

Question 9

What is Data Science course?

Accepted Answer

Data Science is a broad field and you need to learn about so many concepts if you are a beginner. A Data Science course is a training program of around six to twelve months, often taken by industry experts to help candidates build a strong foundation in the field. Apart from the theoretical material, an online data science course includes virtual labs, industry projects, interactive quizzes, and practice tests which can give you enhanced learning experience.

Question 10

Will this course help me to learn Data Science from scratch?

Accepted Answer

Professionals who do not have any prior knowledge of the field can easily begin with this Data Scientist Master’s program as you’ll gain a thorough knowledge of the basic concepts as well.

Course	Course completion certificate	Criteria
Data Science and Statistics Fundamentals	Required	85% of Online Self-paced completion
Data Science with R	Required	85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom, and score above 75% in the course-end assessment, and successful evaluation in at least 1 project
Data Science with SAS	Required	85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom, and score above 75% in the course-end assessment, and successful evaluation in at least 1 project
Data Science with Python	Required	85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom, and score above 75% in course-end assessment and successful evaluation in at least 1 project
Machine Learning and Tableau	Required	85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom, and successful evaluation in at least 1 project
Big Data Hadoop and Spark Developer	Required	85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom, and score above 75% in the course-end assessment, and successful evaluation of at least 1 project
Capstone Project	Required	Attendance of 1 Live Virtual Classroom and successful completion of the capstone project

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