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:
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:
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
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
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.
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.
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.
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.
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.
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.
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:
If individuals are looking to enroll and get the best out of this Data Scientist Course in Munchen, they’d need
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 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.
Kickstart your learning of Python for Data Science with this Data Scientist course and familiarize yourself with programming, tastefully crafted by IBM.
This Data Science with Python course gives you a complete overview of Python’s data analytics tools and techniques. Learning python is a crucial skill for many data science roles, and you can develop it with this Python data science course. With a blended learning approach, you can learn Python for data science along with concepts like data wrangling, mathematical computing, and more. Unlock your career as a data scientist with Simplilearn’s Data Science with Python training.
Ensure career success with this Machine Learning course. Learn this exciting branch of Artificial Intelligence with a program featuring Applied Learning, interactive labs, 4 hands-on projects, and mentoring. With our Machine Learning training, master Machine Learning concepts are required for a Machine learning certification. This Machine Learning online course will provide you with the skills needed to become a successful Machine Learning Engineer today.
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 through our Tableau training and gain job-ready skills. Tableau certification is highly regarded by companies for data-related jobs and our Tableau online course trains you to use the tool effectively for preparing data, creating interactive dashboards, adding different dimensions, and drilling into outliers.
Simplilearn’s Data Science Capstone project will give you an opportunity to implement the skills you learned in the Data Science course. 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 Data Science training and will help you to show your expertise in Data Science to employers.
Our course is exhaustive and this Data Science certification is proof that you have taken a big leap in mastering the domain.
The knowledge and Data Science skills you've gained working on projects, simulations, case studies will set you ahead of the competition.
Talk about your Data Science certification on LinkedIn, Twitter, Facebook, boost your resume, or frame it - tell your friends and colleagues about it.
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 helped me in applying Data Science to my current role of a Traffic Engineer.
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 course completion, I was able to change my job role from a Hadoop Developer to a Big Data Engineer with a good salary hike.
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.
In a Data Science course, you will learn about many concepts if you are a beginner or an intermediate. This training program is around six to twelve months, often taken by industry experts to help candidates build a strong foundation in the field. Besides the theoretical material, our Data Science course includes virtual labs, industry projects, interactive quizzes, and practice tests, giving you an enhanced learning experience.
Data science is a broad field that involves dealing with large volumes of data to uncover hidden trends and patterns and extract valuable information that aids in better decision-making. Companies that collect massive amounts of data use various data science tools and techniques to build predictive models. Simplilearn’s Data Science training can help you learn all its concepts from scratch.
A Data Scientist is an individual who gathers, cleans, analyzes, and visualizes large datasets to draw meaningful conclusions and communicate them to business leaders. The data is collected from various sources, processed into a format suitable for analysis, and fed into an analytics system where statistical analysis is performed to gain actionable insights.
These Data Science courses, co-developed with IBM, will give you an insight into Data Science tools and methodologies, which is enough to prepare you to excel in your next role as a Data Scientist. This Data Science training will teach you R, Python, Machine Learning techniques, data reprocessing, regression, clustering, data analytics with SAS, data visualization with Tableau, and an overview of the Hadoop ecosystem. You will earn an industry-recognized certificate from IBM and Simplilearn that will attest to your new skills and on-the-job expertise.
Professionals with no prior knowledge of the field can easily begin with this Data Science course, as you’ll gain a thorough knowledge of the basic concepts as well.
Yes, this Data Science course is suitable for recent graduates and experienced professionals willing to start a career in data science.
There are no specific eligibility requirements to take this Data Science training.
Learners need to possess an undergraduate degree or a high school diploma. Basic knowledge of statistics and a basic understanding of any programming language is recommended.
This Data Science training will familiarize you with programming languages like Python, R, and Scala and data science tools like Apache Spark, HBase, Sqoop, Hadoop, and Flume.
After completing the payment, you will be notified of your successful enrollment through email. It will give you all the details regarding accessing the Data Science course material. Following the steps, you can go through the video lessons instantly.
Companies are embracing digital transformation, and the growing dependency on data makes a career in data science quite promising. Businesses are accelerating their digital initiatives, and data science skills will remain in high demand soon. Moreover, with the existing skills gap, companies are even ready to pay higher salaries to data scientists. With Simplilearn’s Data Scientist course, you can qualify for this rewarding career.
Data science is a vast field; people cannot gain expertise within six months or a year. Learning data science requires specialized technical skills and knowledge of programming basics and analytics tools to get started. However, this Data Science course explains all the relevant concepts from scratch, making it easy to use your new skills.
Simplilearn’s Data Science course is unique because of the following major features:
As a part of this Data Science online course, in collaboration with IBM, you will receive the following:
Following are the list of courses for which you will get IBM certificates:
The course completion certificate received after completing this Data Science course does not expire.
Upon completion of 80% of LVC hours and 2 projects, you will be eligible to receive the Data Scientist Master’s certificate that will testify to your skills as an expert in Data Science. Please find the individual course criteria given below
|Data Science with Python||
|85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom, and pass 1 project|
|Deep Learning with Keras and TensorFlow||
Data Science Capstone Project
Attendance of 1 Live Virtual Classroom and successful completion of the capstone project
You can enroll in this Data Science training on our website and make an online payment using any of the following options:
Once payment is received, you will automatically receive a payment receipt and access information via email.
Contact us using the form on the right of any page on the Simplilearn website, select the Live Chat link, or Request a callback.
Yes, we do offer a money-back guarantee for many of our training programs. Refer to our Refund Policy and submit refund requests via our Help and Support portal.
All of our highly qualified Data Science trainers are industry experts with years of relevant industry experience. Each of them has gone through a rigorous selection process that includes profile screening, technical evaluation, and a training demo before they are certified to train for us. We also ensure that only those trainers with a high alumni rating remain on our faculty.
Our teaching assistants are a dedicated team of subject matter experts to help you get certified in Data Science on your first attempt. They engage students proactively to ensure the course path is being followed and help you enrich your learning experience, from class onboarding to project mentoring and job assistance. Teaching Assistance is available during business hours.
We offer 24/7 support through email, chat, and calls. We also have a dedicated team that provides on-demand assistance through our community forum. What’s more, you will have lifetime access to the community forum, even after completion of your Data Science course with us.
Yes, Excel skills are beneficial for Data Scientists, and taking an Excel course can be advantageous. Here's why Excel skills are valuable for Data Scientists and how an Excel course can contribute to their work:
Data Exploration and Analysis: Excel provides a user-friendly interface for initial data exploration and analysis. Data Scientists can use Excel to quickly assess data, perform basic calculations, and gain initial insights. An Excel course helps Data Scientists learn advanced data manipulation techniques, such as using formulas, functions, and pivot tables, to analyze and summarize data effectively.
Data Cleaning and Preprocessing: Data cleaning and preprocessing are crucial steps in data science projects. Excel's data manipulation capabilities, combined with an Excel course, equip Data Scientists with skills to handle missing values, remove duplicates, format data, and perform other data cleaning tasks. These skills are essential for ensuring data quality and preparing data for further analysis.
Data Visualization: Visualizing data is a key aspect of data science, as it helps in communicating insights and findings. Excel offers a range of charting and graphing tools that Data Scientists can utilize to create meaningful visualizations. An Excel course teaches Data Scientists how to create visually appealing charts, customize visuals, and present data effectively.
Quick Prototyping and Analysis: Excel's familiarity and ease of use make it a valuable tool for quick prototyping and analysis. Data Scientists can use Excel to perform exploratory data analysis, conduct preliminary modeling, and test hypotheses. An Excel course provides Data Scientists with efficient techniques, shortcuts, and best practices for faster analysis and prototyping.
Collaboration and Communication: Excel is widely used in organizations, making it a common tool for collaboration and communication. Data Scientists can share Excel files, collaborate on data analysis tasks, and integrate Excel outputs into reports or presentations. An Excel course equips Data Scientists with skills for collaborating on workbooks, tracking changes, and effectively sharing insights with team members and stakeholders.
While specialized tools and programming languages are commonly used in advanced data analysis and modeling, Excel skills are still valuable for various data manipulation, exploration, and visualization tasks. By taking an Excel course, Data Scientists can enhance their Excel skills and leverage them strategically throughout different stages of their data science projects.