University of London
IBM
Data Science Foundations Specialization
University of London
IBM

Data Science Foundations Specialization

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.

Romeo Kienzler
Robert Zimmer
Joseph Santarcangelo

Instructors: Romeo Kienzler

Included with Coursera Plus

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Get in-depth knowledge of a subject
4.7

(353 reviews)

Beginner level
No prior experience required
3 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
4.7

(353 reviews)

Beginner level
No prior experience required
3 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers

What you'll learn

  • 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.

Overview

What’s included

Shareable certificate

Add to your LinkedIn profile

Taught in English
117 practice exercises

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from University of London

Specialization - 8 course series

What you'll learn

  • 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.

Skills you'll gain

Data Science, Unsupervised Learning, Machine Learning, Data Literacy, Data Analysis, Applied Machine Learning, and Big Data

What you'll learn

  • 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.

Skills you'll gain

Data Science, Big Data, Cloud Computing, Deep Learning, Machine Learning, Data Analysis, Digital Transformation, Data Mining, Data-Driven Decision-Making, Data Literacy, and Artificial Intelligence

What you'll learn

  • 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. 

Skills you'll gain

Jupyter, GitHub, R Programming, Machine Learning, Data Visualization Software, Git (Version Control System), Big Data, Cloud Computing, Computer Programming Tools, IBM Cloud, Other Programming Languages, Statistical Programming, Version Control, Data Science, Open Source Technology, Query Languages, Development Environment, Python Programming, and R (Software)

What you'll learn

  • In this course you will learn the history of algorithms, discretisation and pseudocode and Euclidean algorithm in pseudocode.

Skills you'll gain

Algorithms, Computer Science, Pseudocode, Computational Thinking, Program Development, and Data Structures

What you'll learn

  • Develop a foundational understanding of Python programming by learning basic syntax, data types, expressions, variables, and string operations.

  • Apply Python programming logic using data structures, conditions and branching, loops, functions, exception handling, objects, and classes.

  • Demonstrate proficiency in using Python libraries such as Pandas and Numpy and developing code using Jupyter Notebooks.

  • Access and extract web-based data by working with REST APIs using requests and performing web scraping with BeautifulSoup.

Skills you'll gain

Python Programming, Pandas (Python Package), Web Scraping, NumPy, Data Structures, JSON, Jupyter, Object Oriented Programming (OOP), Data Manipulation, Application Programming Interface (API), Data Import/Export, Computer Programming, Data Analysis, Scripting, Data Processing, Restful API, Programming Principles, and Automation

What you'll learn

  • In this course you will engage in a variety of mathematical and programming exercises while completing a data clustering project.

Skills you'll gain

NumPy, Data Manipulation, Matplotlib, Pandas (Python Package), Descriptive Statistics, Python Programming, Unsupervised Learning, Data Analysis, Machine Learning Algorithms, Data Science, Statistics, Data Visualization Software, Statistical Analysis, Probability & Statistics, and Jupyter

What you'll learn

  • In this course you will tackle a prediction problem: forecasting the number of bicycles that will be rented on a given day.

Skills you'll gain

Predictive Modeling, Regression Analysis, Correlation Analysis, Data Collection, Data Analysis, Time Series Analysis and Forecasting, Statistical Modeling, Data-Driven Decision-Making, Exploratory Data Analysis, Data Science, and Forecasting

What you'll learn

  • 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.

Skills you'll gain

Web Scraping, Data Manipulation, Data Analysis, Python Programming, Data Science, Matplotlib, Jupyter, Data Processing, Pandas (Python Package), Data Collection, and Dashboard

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Romeo Kienzler
IBM
10 Courses794,466 learners
Robert Zimmer
University of London
5 Courses16,142 learners
Joseph Santarcangelo
IBM
36 Courses2,197,000 learners
Alex Aklson
IBM
21 Courses1,346,336 learners
Rav Ahuja
IBM
56 Courses4,382,472 learners
Azim Hirjani
IBM
1 Course301,388 learners
Aije Egwaikhide
IBM
6 Courses755,050 learners

Offered by

University of London
IBM

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