(All online course fees are in USD)

Course Description

This Data Scientist course is offered in collaboration with IBM, with exclusive hackathons & masterclasses organized by IBM included. This Course is ranked as The No. 1 Data Analytic Course by Career Karma.

The course entails extensive training on Data Science and related tools, such as R, SAS, Python, Tableau, Hadoop, and Spark. Our Data Scientist course is highly practical. This course includes 20+ Data Analytics projects, such as Banking, eCommerce, Technology, & Manufacturing. This would vastly raise your ability to apply data science skills to real-life business setting.

Course Delivery

• Total duration of self-paced online videos learning (SPL) and Live Virtual Classes (LVCs): 125+ hours

Skills Covered

• Data Analytics
• Statistical Analysis using Excel
• Data Analysis using Python and R
• Data Visualization Tableau and Power BI
• Linear and logistic regression modules
• Clustering using KMeans
• Supervised Learning
• Unsupervised Learning

Tools Covered

Skills to be Learned

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

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 – Python for Data Science
  

• Course 2 – Applied Data Science with Python
  

• Course 3 – Machine Learning
  

• Course 4 – Tableau Training
  

• Course 5 – Data Science Capstone

Electives

• SQL Training
• Data Science with R Programming
• Deep Learning with Keras and TensorFlow
• Industry Master Class – Data Science

Advisory board member

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

This course helped a lot. It made me understand how to prioritize important stuff for you. It allowed me to learn and discuss new things like Data Science, Artificial Intelligence, and machine learning. I would also recommend attending Simplilearn’s live classes; they give a lot of contexts and are 10x more helpful.

The trainers are very professional and friendly. They have good knowledge of AI/ML and helped me a lot at the beginning of the course as I was completely new to it. After this course, I learned about the various advancements in the field of AI/ML. I am now recognized as a Subject Matter Expert in AI/ML by my organization.

I had an incredible journey completing my Master’s Certificate in Data Science. Friends, faculty members, and community support encouraged me to complete this achievement. I’ve learned multiple scripting languages and expanded my knowledge in statistics, data management/visualization, and machine learning through IBM and Simplilearn.

The entire content is very organized. I got sufficient practical exposure through the live sessions and projects. The course had more implementation than the theoretical part, which helps understand various concepts better. This certification helped me in applying Data Science to my current role of a Traffic Engineer.

Completing the course has really helped me to fast-track my career in my field of interest and has also upped my confidence.

I had 11-12 years of experience in Business Analysis & Project Management but after the course, I moved to Data Science. This was a great switch for me and I found my niche.

My experience of learning with Simplilearn was great and I was able to achieve my goal of getting a job as well.

Upskilling with Simplilearn was a great experience that also resulted in a new job opportunity for me with a good salary hike.

Simplilearn is a gateway for people who want to enter into the fields of Data Science, AI or Cloud. I found this is to be one of the best online instructor-led portals, and I would definitely recommend it. After the certification, I was able to change my job role from a Hadoop Developer to a Big Data Engineer with a good salary hike.

Simplilearn is an incredible platform to learn on your own, depending on your availability. All the questions raised about projects are resolved quickly, helping students to complete projects in time.

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 learn the concepts better. Thanks to Simplilearn.

I encountered problems when trying to solve the projects in my Data Science class for Python. The Teaching Assistant was accommodating and provided step-by-step guidance through web chat sessions to resolve the issues.

Simplilearn is the best platform for e-learning. The instructors are qualified and knowledgeable and willing to help. I have started with this course, and have finished three courses in the past. I would recommend Simplilearn to my friends and colleagues.

With the help of Simplilearn, I was able to get my first job in a well-reputed company with a great starting package.