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

Sponsored by Coursera Learning Team

Get in-depth knowledge of a subject
4.7

(70 reviews)

Beginner level
No prior experience required
3 months
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.7

(70 reviews)

Beginner level
No prior experience required
3 months
at 10 hours a week
Flexible schedule
Learn at your own pace

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.

Skills you'll gain

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Taught in English
Recently updated!

October 2024

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Specialization - 8 course series

The Data Science Profession – Student View

Course 14 hours4.8 (10 ratings)

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.

What is Data Science?

Course 211 hours4.7 (73,458 ratings)

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.

Tools for Data Science

Course 318 hours4.5 (29,289 ratings)

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. 

What you'll learn

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

Python for Data Science, AI & Development

Course 525 hours4.6 (39,078 ratings)

What you'll learn

  • 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.

What you'll learn

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

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.

Python Project for Data Science

Course 88 hours4.5 (4,394 ratings)

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

Category: Python Programming

Instructors

Romeo Kienzler
IBM
10 Courses708,410 learners
Robert Zimmer
University of London
5 Courses6,011 learners
Joseph Santarcangelo
IBM
33 Courses1,704,068 learners

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IBM

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