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 applied learning, making them experts in AI and Data Science. The Data Science course in Oslo and in collaboration with IBM will make students industry-ready for AI and Data Science job roles.
According to the Forrester Wave report, September 2018, IBM is the world’s second-largest Predictive Analytics and Machine Learning solutions provider. Simplilearn, in collaboration with IBM, will introduce you to the concept of integrated applied learning, helping you gain expertise in AI and Data Science. The Data Science course in Oslo, in collaboration with IBM help students become job-ready in AI and Data Sciene-related job roles and industries.
IBM, headquartered in Armonk, New York, is a premier cognitive solutions and cloud platform company, which offers a wide range of technology and consulting services. IBM invests $6 billion annually into research and development. The company 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 will these Data Science courses developed in collaboration with IBM give me?
Once your Data Scientist course in Oslo reaches fruition, you will receive certificates from IBM and Simplilearn. These certificates, earned from the Data Science training in Oslo, verify your skills as a Data Science expert, and show that you’ve finished your Data Science training in Oslo. You will also gain:
Data Scientist is one of today’s most popular professions. IBM predicts Data Scientist’s demand will increase by 28% in 2020. Our indepth Data Science course in Oslo, co-developed with IBM, will help you gain expertise of the key data science concepts and skills including data wrangling and visualization, data mining, clustering, statistics, regression models, decision trees, hypothesis testing, Spark, Hadoop, PROC SQL, logistic and linear regression, SAS Macros, supervised and unsupervised learning, etc.
This Data Scientist training in Oslo, co-developed with IBM, deals with extensive Data Science training, fusing online instructor-led classes and self-paced learning. The program ends with a capstone project made to reinforce your extensive learning by creating a real industry product that encompasses all of the key aspects you learned throughout the program. These skills will prepare you for the role of a Data Scientist.
The comprehensive Data Science training in Oslo will also help you gain real-life experience with its 15 industry projects based on different industry sectors and domains. These projects help you master concepts of Data Science and Big Data. Here are a few of the projects:
Capstone Project:
Description: You will go through dedicated mentor classes to create a high-quality industry project, solving a real-world problem by leveraging the skills and technologies learned throughout the program. The capstone project in this data science course in Oslo covers all the key points of data extraction, cleaning, and visualization, to model building and tuning. You will also be able to choose the domain/industry dataset you wish to work on, based on the options available.
Upon successful submission of the project you will get a capstone certificate, that you can share with potential employers as a proof of your expanded learning from this data science training in Oslo.
Project 1: Products rating prediction for Amazon
Domain: E-commerce
Amazon, one of the leading US-based e-commerce companies, typically recommends products that fall in the same category to customers, based on the latter’s activity and reviews of similar products. Amazon wants to improve this recommendation engine by expanding it to predict ratings for the non-rated products and adding them to customer 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 their customers’ experience by identifying problem areas that lower customer satisfaction, and act on these issues. The company is also seeking key recommendations that they can implement 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, wants you to identify the factors that influence employee attrition. Based on the parameters identified, the company also wants to build a logistics regression model that helps predict employee churn rate.
Project 4: Predict accurate sales for 45 Walmart stores, considering the impact of promotional markdown events. Walmart is one of the leading US-based retail stores. Determine if macroeconomic factors like CPI, unemployment rate, etc., impact sales.
Domain: Retail
Description: Walmart runs many promotional markdown events during the year. The markdowns typically precede prominent holidays and events like the Super Bowl, Labor Day, Thanksgiving, and of course, Christmas. The weeks where these holidays fall are weighted five times higher in valuation than ordinary weeks. The business, however, is facing a challenge due to unexpected demand, resulting in stocks running out at times, exacerbated by inaccurate demand estimation. Macroeconomic factors like CPI, Unemployment Index, etc. also play an important role in predicting demand, but the company hasn’t yet been able to leverage these factors. Part of this project requires creating a model to highlight the effects of the markdowns on holiday weeks.
Project 5: Learn how the top healthcare industry leaders make use of Data Science to improve their business.
Domain: HealthCare
Description: Predictive analytics can be used in many different aspects of healthcare, such as mediating hospital readmissions. Regardless of the industry, predictors are most useful when they can be turned into action. In other words, historical and real-time data alone are worthless without the company making a move. More importantly, in order to judge the value and efficiency of forecasting a trend and ultimately altering behavior, both the predictor and the intervention must be incorporated back into the same workflow and system where the trend originally began.
Project 6: Grasp how Insurance leaders like AIG, AXA, Berkshire Hathaway, etc., use Data Science by working on an insurance-based real-life project in this data science course in Oslo.
Domain: Insurance
Description: According to the 2013 Insurance Predictive Modeling Survey, predictive analytics has increased greatly in the insurance industry, especially for the biggest companies. Although the survey showed an increase in predictive modeling across the industry, every company that writes over $1 billion in personal insurance employs predictive modeling, compared to just 69% of the companies who deal with less than that premium amount.
Project 7: See how large banks like Bank of America, Citigroup, ICICI, HDFC, etc. use Data Science to stay ahead of the competition.
Domain: Banking
Description: A Portuguese banking institution conducted a marketing campaign to give potential customers incentive to invest in a bank term deposit. The bank’s marketing campaigns were conducted via phone calls. However, sometimes the same customer was contacted more than once. Your job is to analyze all the data collected from this marketing campaign.
Project 8: Learn how stock markets like NASDAQ, NSE, and BSE leverage Data Science and Analytics to derive consumable data from complex datasets.
Domain: Stock Market
Description: You must import data using Yahoo data reader from the following companies: Apple, Amazon, Microsoft, Google, and Yahoo. You must then perform fundamental analytics functions, such as performing daily return analysis, plotting stock trade by volume, plotting closing price, and using pair plot to show the stocks’ correlations.
Project 9: Understand how Data Science is used in the field of engineering by engaging in this case study of MovieLens Dataset Analysis.
Domain: Engineering
Description: The GroupLens Research Project is a research group in University of Minnesota’s Department of Computer Science and Engineering. The group’s researchers are involved in several research projects related to the fields of collaborative filtering, information filtering, and recommender systems.
Project 10: See 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: Companies use Analytics to optimize product placements on their shelves or optimize the inventory in their warehouses. 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.
Data Scientists require a mixture of experience, data science knowledge, and the correct tools and technologies. It’s a strong career choice ideal for both new and experienced professionals alike. Professionals with a decent data analytics background are best suited to take the Data Science course in Oslo and for the given positions:
Any learner looking to extract the best value out of Simplilearn’s Data Scientist Course in Oslo, would need to possess;
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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.
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.