Data Scientist Course in Oxford

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 Oxford 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 along with IBM, will introduce students to the new-age concept of integrated applied learning, helping them gain expertise in AI and Data Science at an accelerated pace. The Data Science certification in Oxford, 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?

After you complete the Data Scientist course in Oxford, you will receive certificates from IBM and Simplilearn. These certificates, earned from the Data Science training in Oxford, verify your skills as a Data Science expert, and show that you’ve finished your Data Science training in Oxford. You will also gain:

• Access anytime to IBM’s cloud platforms, including IBM Watson and other applications for practice
• Simplilearn’s industry-recognized Data Scientist Master's certificate

Data Scientist is one of today’s most popular professions. IBM predicts Data Scientist’s demand will increase by 28% in 2020. The comprehensive Data Science course in Oxford, in collaboration with IBM, will help you ace the advanced 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 Oxford, 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.

• Acquire an in-depth understanding of data structure and manipulation
• Learn about and how to use linear and non-linear regression models and classification techniques dedicated to data analysis
• Gain an in-depth knowledge of supervised and unsupervised learning models like clustering, dimensionality reduction, linear regression, logistic regression, K-NN, and pipeline
• Conduct technical and scientific computing with the SciPy package and its sub-packages like Integrate, Optimize, Statistics, IO, and Weave, for example.
• Obtain expertise in the field of mathematical computing using the NumPy and Scikit-Learn packages
• Become familiar with the different components of the Hadoop ecosystem
• Gain experience working with HBase, its architecture, and data storage. Learn to tell the difference between HBase and RDBMS, and conduct partitioning using Hive and Impala
• Understand MapReduce and all its characteristics, and learn how to ingest data using tools like Sqoop and Flume
• Master the underlying concepts of the recommendation engine and time series modeling. Get practical mastery over the algorithms, principles, and applications of machine learning
• Learn how to analyze data using Tableau, and become skilled in building interactive dashboards in this data science training in Oxford

Our bootcamp program offering Data Science training in Oxford 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 Oxford 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 submitting 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 Oxford.

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 Oxford.
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. If you come from an analytics background you can easily fit into the Data Science course in Oxford and for the given positions:

• 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

Any learner looking to extract the best value out of Simplilearn’s Data Scientist Course in Oxford, would need to possess;

• A basic understanding of Statistics and its concepts
• Understanding of at least of the top/relevant programming languages

When you’ve successfully completed Simplilearn’s Data Science course in Oxford, what you’d have is a set of highly specialized and in-demand data science skills sought after today for top job roles such as:

• Data Analytics Expert
• Data Scientist 
• Analytics Head/Lead/Manager 
• Specialist - Statistical Programming
• Machine Learning(ML) Engineer

Data Scientists are the top-ranking professionals in any analytics organization, and the Glassdoor job site ranks Data Scientists second in the 50 Best Jobs for 2021. Data Scientists are scarce and in demand in today’s IT job market. As a Data Scientist, you must understand and analyze business problems, build data analysis strategies, gain insights from the given dataset, and give solutions backed by data. Hence taking a Data Science course in Oxford is a pluspoint for all the aspiring professionals.