Expert Programmes

Data Scientist – Master Certification Programme

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$1,299.00 $1,104.00
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(All online course fees are in USD)

 

Course Description

This Data Scientist Master’s Program in collaboration with IBM accelerates your career in Data Science providing you with worldclass training and skills required to become successful in this domain.

The programme offers extensive training on the most in-demand Data Science and Machine Learning skills with hands-on exposure to key tools and technologies including R, SAS, Python, Tableau, Hadoop, and Spark. Become an expert in Data Science by deep diving into the nuances of data interpretation, interworking technologies like Machine Learning, and mastering powerful programming skills to take your career in Data Science to the next level.

 

Developed /Co-Developed by
IBM & Simplilearn

 

Offered in Partnership with

Simplilearn

 

Course Delivery
  • Online self-paced learning
  • Virtual classroom training

Total online blended learning:   hours

Benefits
  • Portfolio worthy capstone demonstrating mastered concepts
  • 30+ In-demand skills
  • 15+ Real-life projects providing hands-on industry training

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.

 

Skills to be Learned
  • 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

 

Award upon Successful Completion
  • “Certificate of Achievement” in “Data Scientist” issued by Simplilearn
  • IMB Watson for Chatbots certificate of completion issued by IBM, if this elective is selected

 

Awarding Organisations
IBM / Simplilearn

 

 

Data Scientist

Learning Outcomes
  • 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 package
  • 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 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

 

Assessments

Beside course-end quizzes, this Data Scientist Master’s program also 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 a 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.

 

Who Should Enrol

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

 

Prerequisites

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

  • Basic knowledge of statistics
  • Basic understanding of any programming language

 

Course Overview
  • Course 1 – Data Science Certification Training – R Programming
  • Course 2 – Data Science with Python
  • Course 3 – Machine Learning
  • Course 4 – Tableau Training
  • Course 5 – Big Data Hadoop and Spark Developer
  • Course 6 – Data Science Capstone

 

Electives
  • IBM Watson for Chatbots

This course provides a practical introduction on how to build a chatbot with Watson Assistant without writing any code and then deploy your chatbot to a real website in less than five minutes. It will teach you to plan, build, test, analyze, and deploy your first chatbot.

  • Machine Learning with R

In this course, you will learn how to write R code, learn about R’s data structures, and create your own functions.

With the knowledge gained, you will be ready to undertake your first very own data analysis. You would further learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each using R.

 

Advisory board member
Ronald van Loon
Ronald Van Loon

Big Data Expert, Director Adversitement
Named by Onalytica as one of the 3 most influential people in Big Data, Ronald is an author for a number of leading Big Data and Data Science websites, including Datafloq, Data Science Central, and The Guardian. He is also a renowned speaker at industry events.

 

Accessible Period of Course

1 Year from date of enrolment

 

Customer Reviews
Tajuddin Shaik

I enrolled in the Simplilearn Masters Program for Data
Science to enhance my career and it was a great
experience. The courses are delivered by very qualified
and experienced trainers, who provided an excellent
learning experience. The courses are accessible
through the Simplilearn App for any time access. Yes,
and 5 Star customer service.

 

Pramod Bhargav

Sr. Business Data Analyst and Lead
The trainer was entirely professional, knowledgeable,
and helpful while clearing any doubts. Worth the
money and time spent to learn from Simplilearn.

 

Deepika Vashishtha

The study material provided is perfect. And you get
lab access on top of that which is very important
when trying to learn big data technologies. I also
found the live classes very beneficial. The projects
and assignments provided help us

 

 

 

Course Features

  • Students 0 student
  • Max Students1000
  • Duration404 hour
  • Skill levelall
  • LanguageEnglish
  • Re-take course20000
  • Course 1 - Data Science Certification Training - R Programming

    Simplilearn’s Data Science certification with R Programming training makes you an expert in data analytics using the R programming language. This course enables you to take your Data Science skills into a variety of companies, helping them analyze data and make more informed business decisions.

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  • Course 2 - Data Science with Python

    The Data Science with Python course provides a complete overview of Data Analytics tools and techniques using Python. Learning Python is a crucial skill for many Data Science roles. Acquiring knowledge in Python will be the key to unlock your career as a Data Scientist.

    No items in this section
  • Course 3 - Machine Learning

    Explore the concepts of Machine Learning and understand how it’s transforming the digital world. An exciting branch of Artificial Intelligence, this Machine Learning certification online course will provide the skills you need to become a Machine Learning Engineer and unlock the power of this emerging field.

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  • Course 4 - Tableau Traning

    This Tableau certification course helps you master Tableau Desktop, a world-wide utilized data visualization, reporting, and business intelligence tool. Advance your career in analytics by learning Tableau and how to best use this training in your work.

    No items in this section
  • Course 5 - Big Data Hadoop and Spark Developer

    Our Big Data Hadoop certification training course lets you master the concepts of the Hadoop framework, Big Data tools, and methodologies to prepare you for success in your role as a Big Data Developer. Learn how various components of the Hadoop ecosystem fit into the Big Data processing lifecycle.

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  • Course 6 - Data Science Capstone

    Simplilearn’s Data Science Capstone project will give you an opportunity to implement the skills you learned in the Data Scientist Master’s Program. Through dedicated mentoring sessions, you’ll learn how to solve a real-world, industry-aligned data science problem, from data processing and model building to reporting your business results and insights. The project is the final step in the Data Scientist Master's Program and will help you to show your expertise in data science to employers.

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