Data Science Foundations

University of London via Coursera Specialization

Overview

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!

Syllabus

Course 1: The Data Science Profession – Student View
- Offered by University of London and IBM. This course is primarily aimed at individuals who want to learn how Data Science is applied in the ... Enroll for free.

Course 2: What is Data Science?
- Offered by University of London and IBM. Do you want to know why data science has been labeled the sexiest profession of the 21st century? ... Enroll for free.

Course 3: Tools for Data Science
- Offered by University of London and IBM. In order to be successful in Data Science, you need to be skilled with using tools that Data ... Enroll for free.

Course 4: Problems, Algorithms and Flowcharts
- Offered by University of London and IBM. This course is the fourth of eight courses aiming to help you to become confident working with ... Enroll for free.

Course 5: Python for Data Science, AI & Development
- Offered by University of London and IBM. Kickstart your learning of Python with this beginner-friendly self-paced course taught by an ... Enroll for free.

Course 6: Statistics and Clustering in Python
- Offered by University of London and IBM. This course is the sixth of eight courses. This project provides an in-depth exploration of key ... Enroll for free.

Course 7: Data Science Project Capstone: Predicting Bicycle Rental
- Offered by University of London and IBM. This course is the seventh of eight. In this project, we will tackle a prediction problem: ... Enroll for free.

Course 8: Python Project for Data Science
- Offered by University of London and IBM. This mini-course is intended to for you to demonstrate foundational Python skills for working with ... Enroll for free.

Courses

4 reviews
11 hours 27 minutes
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Do you want to know why data science has been labeled the sexiest profession of the 21st century? After taking this course, you will be able to answer this question, understand what data science is and what data scientists do, and learn about career paths in the field. The art of uncovering insights and trends in data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and accurately predicted the Nile River's flooding every year. Since then, people have continued to use data to derive insights and predict outcomes. Recently, they have carved out a unique and distinct field for the work they do. This field is data science. In today's world, we use Data Science to find patterns in data and make meaningful, data-driven conclusions and predictions. This course is for everyone and teaches concepts like how data scientists use machine learning and deep learning and how companies apply data science in business. You will meet several data scientists, who will share their insights and experiences in data science. By taking this introductory course, you will begin your journey into this thriving field.
3 reviews
18 hours 48 minutes
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In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ as part of their jobs. This course teaches you about the popular tools in Data Science and how to use them. You will become familiar with the Data Scientist’s tool kit which includes: Libraries & Packages, Data Sets, Machine Learning Models, Kernels, as well as the various Open source, commercial, Big Data and Cloud-based tools. Work with Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. You will understand what each tool is used for, what programming languages they can execute, their features and limitations. This course gives plenty of hands-on experience in order to develop skills for working with these Data Science Tools. With the tools hosted in the cloud on Skills Network Labs, you will be able to test each tool and follow instructions to run simple code in Python, R, or Scala. Towards the end the course, you will create a final project with a Jupyter Notebook. You will demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.
3 reviews
1 day 1 hour 3 minutes
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Kickstart your learning of Python with this beginner-friendly self-paced course taught by an expert. Python is one of the most popular languages in the programming and data science world and demand for individuals who have the ability to apply Python has never been higher. This introduction to Python course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn about Python basics and the different data types. You will familiarize yourself with Python Data structures like List and Tuples, as well as logic concepts like conditions and branching. You will use Python libraries such as Pandas, Numpy & Beautiful Soup. You’ll also use Python to perform tasks such as data collection and web scraping with APIs. You will practice and apply what you learn through hands-on labs using Jupyter Notebooks. By the end of this course, you’ll feel comfortable creating basic programs, working with data, and automating real-world tasks using Python. This course is suitable for anyone who wants to learn Data Science, Data Analytics, Software Development, Data Engineering, AI, and DevOps as well as a number of other job roles.
0 reviews
8 hours 30 minutes
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This mini-course is intended to for you to demonstrate foundational Python skills for working with data. This course primarily involves completing a project in which you will assume the role of a Data Scientist or a Data Analyst and be provided with a real-world data set and a real-world inspired scenario to identify patterns and trends. You will perform specific data science and data analytics tasks such as extracting data, web scraping, visualizing data and creating a dashboard. This project will showcase your proficiency with Python and using libraries such as Pandas and Beautiful Soup within a Jupyter Notebook. Upon completion you will have an impressive project to add to your job portfolio. PRE-REQUISITE: **Python for Data Science, AI and Development** course from IBM is a pre-requisite for this project course. Please ensure that before taking this course you have either completed the Python for Data Science, AI and Development course from IBM or have equivalent proficiency in working with Python and data. NOTE: This course is not intended to teach you Python and does not have too much instructional content. It is intended for you to apply prior Python knowledge.
0 reviews
7 hours 23 minutes
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This course is the seventh of eight. In this project, we will tackle a prediction problem: forecasting the number of bicycles that will be rented on a given day. Using historical data, we will consider factors such as weather conditions, the day of the week, and other relevant variables to accurately predict daily bicycle rentals. This will help ensure that our bicycle rental service is prepared with the appropriate number of bicycles each day. We will learn specifically about data acquisition and correlation.
0 reviews
8 hours 11 minutes
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This course is the fourth of eight courses aiming to help you to become confident working with algorithms and data structure. You will learn the history of algorithms, discretisation and pseudocode and Euclidean algorithm in pseudocode.
0 reviews
17 hours 51 minutes
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This course is the sixth of eight courses. This project provides an in-depth exploration of key Data Science concepts focusing on algorithm design. It enhances essential mathematics, statistics, and programming skills required for common data analysis tasks. You will engage in a variety of mathematical and programming exercises while completing a data clustering project using the K-means algorithm on a provided dataset.
0 reviews
4 hours 28 minutes
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This course is primarily aimed at individuals who want to learn how Data Science is applied in the real world, what we mean by data, and what we mean by machine learning. The course also covers concepts such as K-means and categorical and numerical data.