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Unlock Academic & Career Success with Data Science. Build the foundational knowledge and hands-on skills you need to forge new career opportunities, with no technical experience required.
Instructors: Romeo Kienzler
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Foundational knowledge and practical understanding of data science that unlocks academic and career opportunities
Basic hands-on skills in Python, R, SQL, and tools like GitHub and Jupyter Notebooks, including their essential features and uses in data science
Foundational data science processes, including data collection, simple model building, and algorithm concepts using flowcharts and pseudocode.
Basic data analysis with Python, using libraries like Pandas and Numpy, creating simple dashboards, and working with clustering algorithms.
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Nearly one in four job postings in the US alone require some data science skills and employers are paying up to 14% more for those skills. (Report : ExcelinEd & the Burning Glass Institute).
This powerful specialisation from the University of London and IBM gives you the perfect academic and industry-informed practical introduction to data science. You get:
- Progress transfer for the University of London’s BSc in Computer Science
- The foundational skills and knowledge you need to get a job in a data-rich environment.
During this specialisation, you’ll be introduced to data science, statistics, programming, computational thinking, machine learning, and more. You’ll discover the role of data science in today’s data-driven world. Plus, you’ll get hands-on using IBM’s data science tools, giving you practical experience to talk about in interviews.
Half the teaching is provided by Goldsmiths, University of London, giving you a strong academic foundation. The other half, designed by IBM, provides real-world professional insight supported by practical projects and a capstone project for your resume.
The “Problems and Algorithms in Data Science” course is a great preview of the BSc Computer Science degree with the opportunity to roll your progress into the degree, if you successfully apply and register.
If you’re looking for a solid, practical understanding of data science that unlocks academic and career opportunities, ENROLL today!
Applied Learning Project
There are two Capstone projects that draw together the material across the Data Science Foundations specialization to enable you to apply what you have learned. In one project, students will tackle a prediction problem: forecasting the number of bicycles that will be rented on a given day. Using historical data, students will consider factors such as weather, the day of the week, and other relevant variables to accurately predict daily bicycle rentals. This will help ensure that the bicycle rental service is prepared with the appropriate number of bicycles each day. Students will learn specifically about data acquisition, linear regression, and correlation. In the other project, students will predict if the Falcon 9 rocket's first stage will land successfully and determine the cost of a launch. In doing so, students will apply skills to perform data collection, data wrangling, exploratory data analysis, data visualization model development, and model evaluation.
In this course you learn how Data Science is applied in the real world, what we mean by data, and what we mean by machine learning.
Define data science and its importance in today’s data-driven world.
Describe the various paths that can lead to a career in data science.
Summarize advice given by seasoned data science professionals to data scientists who are just starting out.
Explain why data science is considered the most in-demand job in the 21st century.
Describe the Data Scientist’s tool kit which includes: Libraries & Packages, Data sets, Machine learning models, and Big Data tools
Utilize languages commonly used by data scientists like Python, R, and SQL
Demonstrate working knowledge of tools such as Jupyter notebooks and RStudio and utilize their various features
Create and manage source code for data science using Git repositories and GitHub.
In this course you will learn the history of algorithms, discretisation and pseudocode and Euclidean algorithm in pseudocode.
Learn Python - the most popular programming language and for Data Science and Software Development.
Apply Python programming logic Variables, Data Structures, Branching, Loops, Functions, Objects & Classes.
Demonstrate proficiency in using Python libraries such as Pandas & Numpy, and developing code using Jupyter Notebooks.
Access and web scrape data using APIs and Python libraries like Beautiful Soup.
In this course you will engage in a variety of mathematical and programming exercises while completing a data clustering project.
In this course you will tackle a prediction problem: forecasting the number of bicycles that will be rented on a given day.
Play the role of a Data Scientist / Data Analyst working on a real project.
Demonstrate your Skills in Python - the language of choice for Data Science and Data Analysis.
Apply Python fundamentals, Python data structures, and working with data in Python.
Build a dashboard using Python and libraries like Pandas, Beautiful Soup and Plotly using Jupyter notebook.
The University of London is a federal University which includes 17 world leading Colleges. With extensive experience in distance learning since 1858, University of London has enriched the lives of thousands of students, delivering high quality degrees across the globe. Today, University of London is a global leader in flexible study, offering degree programmes to over 45,000 students in over 190 countries, delivering world-leading research across the world. To find out more about University of London, visit www.london.ac.uk
At IBM, we know how rapidly tech evolves and recognize the crucial need for businesses and professionals to build job-ready, hands-on skills quickly. As a market-leading tech innovator, we’re committed to helping you thrive in this dynamic landscape. Through IBM Skills Network, our expertly designed training programs in AI, software development, cybersecurity, data science, business management, and more, provide the essential skills you need to secure your first job, advance your career, or drive business success. Whether you’re upskilling yourself or your team, our courses, Specializations, and Professional Certificates build the technical expertise that ensures you, and your organization, excel in a competitive world.
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Earn a degree from world-class universities - 100% online
Upskill your employees to excel in the digital economy
Any one with an interest in Computer Science and Data Science.
No background knowledge is necessary, just GCSE Mathematics (Grade A*-B / 9-5), high school math, or equivalent.
The Specialisation is non credit bearing, however, it provides a 'taster' of one of the modules taken from the University of London BSc Computer Science suite of degrees.
Data science is used in the real world to analyse data, uncover patterns, and make informed decisions. It’s applied in various fields, including healthcare for predicting patient outcomes, finance for detecting fraud, marketing for targeted campaigns, and transportation for optimising routes and predicting demand. By turning raw data into actionable insights, data science helps organisations solve complex problems and improve efficiency.
Basic skills in data science include understanding programming languages like Python or R, working with data analysis tools such as Pandas and SQL, and knowing how to clean, organise, and visualise data. Other foundational skills involve understanding basic statistics, learning machine learning concepts, and using tools like Jupyter Notebooks and GitHub for collaboration and development.
Data science is important in computer science because it enables the analysis and interpretation of vast amounts of data, and can therefore drive innovation and informed decision-making. It combines programming, algorithms, and statistical analysis to extract valuable insights from data, which are crucial for developing smarter systems, improving user experiences, and solving complex problems across various industries. Data science also plays a key role in advancing technologies like artificial intelligence and machine learning.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.
This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.
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