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:
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.
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:
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
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
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.
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.
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.
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.
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.
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.
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:
Any learner looking to extract the best value out of Simplilearn’s Data Scientist Course in Oxford, would need to possess;
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 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.
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.
This comprehensive training incorporates the following Data Science courses:
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 the following minimum requirements, you will be eligible to receive the Data Scientist Master’s certificate that will testify to your skills as an expert in Data Science.
|Data Science with Python||
|85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom, and score above 60% in course-end assessment and successful evaluation in at least 1 project|
85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom, and successful evaluation in at least 1 project
|Deep Learning with Keras and TensorFlow||
Attend 1 Live Virtual Classroom and successful evaluation in at least 1 project and score 70% for course-end assessment
85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom, and successful evaluation in at least 1 project
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.