Data Scientist Training Course in Munich, Germany

As shown in the Forrester Wave report from September 2018, IBM is the second-largest provider of Predictive Analytics and Machine Learning solutions in the world. Simplilearn with this course (offered in collaboration with IBM) trains learners via applied learning providing them with in-demand skills to become experts in Artificial Intelligence and Data Science. The Data Science course in Munchen gets students ready for a rich career in the fields of Artificial Intelligence and Data Science.

Headquartered in Armonk, New York, IBM is a respected leader in premier cognitive solutions and cloud platforms, offering a vast selection of technology and consulting services. The well-established company is an acknowledged leader in research and development, investing $6 billion annually into these fields. IBM has won five Nobel prizes, five US National Medals of Science, six Turing Awards, nine US National Medals of Technology, and 10 inductions into the US Inventors Hall of Fame.

What benefits will this Data Science course in Munchen developed in collaboration with IBM give me?

You will receive certificates from IBM and Simplilearn for their respective courses, once you finish the Data Scientist online Master's program. The certificates that learners earn via our Data Science course in Munchen is proof of their knowledge in in-demand areas of Data Science and proves that they's gone through our Data Science training in Munchen till the end. You will also receive:

• 24/7 access to IBM’s cloud platforms, which also features IBM Watson and other relevant applications suitable for practicing your skills
• Simplilearn’s industry-recognized Data Scientist Master's certificate

The Data Scientist profession is one of the most popular IT-related professions available today. IBM predicts that the need for Data Scientists will increase by 28% in 2020. Our Data Science course in Munchen (delivered as an IBM collaboration) trains you for key skills - data visualizations, clustering, data mining/wrangling, hypothesis testing, decision trees regression models, and linear and logistic regression. The course also explores Hadoop, PROC SQL, SAS Macros, Spark, recommendation engine, supervised and unsupervised learning, and other valuable skills.

The Data Scientist Master’s program focuses on extensive Data Science training, combining online instructor-led classes and relaxed self-paced learning. Our program offering Data Science training in Munchen ends in a Capstone project which is a culmination of all that you've learned by getting you to work on current business problem, and allowing you the chance to apply all your learnings from our bootcamp. All of these skills will help you become an expert Data Scientist.

This Data Science training in Munchen boasts of more than 15 real-life, industry-based projects, emphasizing different domains. These projects help you grasp the more well-used concepts of Data Science and Big Data. Here are some of the projects you will encounter:

Capstone Project:

Description: Dedicating mentoring will be available as you work on an highly industry-relevant project which has you solving real-world business critical problem applying the tools/skills and technologies taught in this bootcamp program. The capstone project includes all the key points of data extraction, cleaning, and visualization, and how to build and tune models. You can also choose the domain/industry dataset you want to work on, based on whatever options are available.

After you successfully submit your project, you will earn a capstone certificate, showcasing your expanded learning and skills to potential employers.

Project 1: Products rating prediction for Amazon
Domain: E-commerce
Amazon, one of the top US-based e-commerce companies, habitually recommends products to customers that fall in categories that mesh with their past product activity and reviews. Amazon intends to enhance its recommendation engine, boost its capabilities - making it capable to predict non-rated product ratings, and subsequently have them added to the user recommendations.

Project 2: Improving customer experience for Comcast
Domain: Telecom
Description: Comcast, one of the top US-based global telecommunication companies, wants to take their customer service experience to the next level by locating problem areas that reduce customer satisfaction. Once these areas are found, Comcast wants a plan on how to solve this dilemma. The company is also looking for useful strategies that they can put in place to deliver the best customer experience. 

Project 3: Attrition Analysis for IBM
Domain: Workforce Analytics
Description: IBM is one of the United States’ oldest and most well-known IT companies. This computer giant wants you to pinpoint the factors that influence employee attrition. Also, using the parameters identified, the company would like to develop a logistics regression model that predicts the employee churn rate.

Project 4: Predict accurate sales for 45 Walmart stores, taking into consideration the impact of promotional markdown events. Walmart is one of America’s main retail stores. Figure out if macroeconomic factors like the Consumer Price Index, unemployment rate, etc., impact their sales.
Domain: Retail
Description: Walmart typically holds several promotional markdown events during the year. These markdowns usually revolve around popular holidays and annual events such as Labor Day, Thanksgiving, the Super Bowl, and of course, Christmas. The weeks with these holidays have a weighing factor five times higher in valuation than the normal, uneventful weeks. Walmart, however, is facing a challenge because of unanticipated demand, a situation made worse thanks to incorrect demand estimation. This flawed estimation results in the occasional stock shortfall. Macroeconomic factors like CPI, Unemployment Index, etc. can play an important role in predicting demand, but the company hasn’t yet figured out how to leverage these factors. Part of this project involves creating a model to highlight the effects of these promotional markdowns on the holiday weeks.

Project 5: Learn how top healthcare industry leaders use Data Science to improve their business in this data science course in Munchen.
Domain: HealthCare
Description: Predictive analytics is a valuable tool for many facets of healthcare, like mediating hospital readmissions, for example. But regardless of the industry, predictors offer the most value when they can be acted upon. In other words, historical and real-time data alone are useless until the company takes appropriate action. Furthermore, in order to predict the value and effectiveness of forecasting a trend and thereby change its behavior, you have to be able to reintroduce both the predictor and the intervention into the same workflow and system where the trend originally began.

Project 6: Work on an insurance-based real-life project to understand how insurance leaders like AIG, AXA, Berkshire Hathaway, etc., use Data Science.
Domain: Insurance
Description: According to data found in the 2013 Insurance Predictive Modeling Survey, predictive analytics have increased noticeably in the insurance industry, especially among the larger companies. The survey shows a predictive modeling boost across the industry, but the trends are inconsistent. For example, every insurance company writing over $1 billion in personal insurance uses predictive modeling, but companies who deal with less than $1 billion are set in the 69% utilization range.

Project 7: See how large banks like Bank of America, Citigroup, ICICI, HDFC, etc. use Data Science to stay ahead of their competition. 
Domain: Banking
Description: A Portuguese banking institution launched a marketing campaign to give potential customers a compelling reason to invest their money in a bank term deposit. The bank used phone calls for this marketing campaign. Unfortunately, sometimes a customer got multiple calls from the campaign. Your job is to analyze all the relevant data obtained from this marketing campaign.

Project 8: Understand how stock markets like NASDAQ, NSE, and BSE leverage Data Science and Analytics to gather consumable data from complex data sets.
Domain: Stock Market
Description: You will use the Yahoo data reader to import data from the following companies: Amazon, Microsoft, Apple, Google, and Yahoo. You must then use this data to perform fundamental analytics functions such as plotting closing price, plotting stock trade by volume, running daily return analysis, and using pair plots to show the correlations between stocks.

Project 9: Learn how Data Science is used in the field of engineering by working on this case study of MovieLens Dataset Analysis.
Domain: Engineering
Description: The GroupLens Research Project is a research group at the University of Minnesota’s Department of Computer Science and Engineering. The researchers are involved in several projects relating to collaborative filtering, information filtering, and recommender systems.

Project 10: Explore how top retail companies like Amazon, Walmart, Target, etc. utilize Data Science to analyze and optimize their product placements and stock inventory.
Domain: Retail
Description: Big businesses use Analytics to optimize their product shelf placement in stores and their warehouse inventory. This project helps participants learn about the daily cycle of product optimization, taking it from the warehouse to the shelves. This cycle provides the company with insights into regular happenings in the retail sector.

The best Data Scientists have an eclectic mixture of experience, data science knowledge, and the associated tools and technologies. It’s a fantastic career path, suitable for rookies and seasoned experts alike. Individuals having a passion for data science, an analytical mindset and good education will make great candidates who will benefit the maximum from our Data Science training in Munchen; they include:

• 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

If individuals are looking to enroll and get the best out of this Data Scientist Course in Munchen, they’d need

• Basic (working level) knowledge of Statistics
• A fundamental grasp of any related programming language

As a successful learner of our globally-recognized Data Science course in Munchen, you would have gathered a skillset that is vital to go after the top and often dreams jobs for many, including:

• Data Scientist 
• Data Analyst
• Manager or Lead - Analytics 
• ML (Machine Learning) Engineer
• Statistical Programming Specialist

Data is everywhere. We use it at work, at home, or when conducting online commerce, and more is generated every day. So, Data Scientists are consequently the highest ranked professionals in any analytics organization. Glassdoor ranks the career of Data Scientist second in the 50 Best Jobs for 2021. There’s a shortage of Data Scientists, so that’s why it’s a great idea to take this data science course in Munchen. A trained data science professional grasp problem statements gather and assimilate data, come up with data analysis strategies, apply algorithms or/and techniques that have high accuracy and consequently reveal insights that can lead to positive actions.