20 courses for a total of approximately 67 hours to get you from beginner Python user to expert data scientist. This set of classes adds to DataCamp’s Data Analyst track, and is designed to go further to Deep Learning and Machine Learning.
While a basic understanding of programming and math are necessary, you can start this class as an absolute beginner and, with consistent practice, finish it ready for a career in data science.
If you are an academic professional, you can sign your class up for an entire semester for free via DataCamp for the Classroom.
Training Course Content
Intro to Python for Data Science
Master the basics of data analysis in Python. Expand your skill set by learning scientific computing with numpy.
Intermediate Python for Data Science
Level up your data science skills by creating visualisations using matplotlib and manipulating data frames with Pandas.
Python Data Science Toolbox (Part 1)
Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.
Python Data Science Toolbox (Part 2)
Continue to build your modern Data Science skills by learning about iterators and list comprehensions.
Importing Data in Python (Part 1)
Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.
Importing Data in Python (Part 2)
Improve your Python data importing skills and learn to work with web and API data.
Cleaning Data in Python
This course will equip you with all the skills you need to clean your data in Python.
Learn how to use the industry-standard pandas library to import, build, and manipulate DataFrames.
Manipulating DataFrames with pandas
You will learn how to tidy, rearrange, and restructure your data using versatile pandas DataFrames.
Merging DataFrames with pandas
This course is all about the act of combining, or merging, DataFrames, an essential part your Data Scientist’s toolbox.
Introduction to Databases in Python
In this course, you’ll learn the basics of relational databases and how to interact with them.
Introduction to Data Visualisation with Python
Learn more complex data visualisation techniques using Matplotlib and Seaborn.
Interactive Data Visualisation with Bokeh
Learn how to create versatile and interactive data visualisations using Bokeh.
Statistical Thinking in Python (Part 1)
Build the foundation you need to think statistically and to speak the language of your data.
Statistical Thinking in Python (Part 2)
Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.
Supervised Learning with scikit-learn
Learn how to build and tune predictive models and evaluate how well they will perform on unseen data.
Machine Learning with the Experts: School Budgets
Learn how to build a model to automatically classify items in a school budget.
Unsupervised Learning in Python
Learn how to cluster, transform, visualise, and extract insights from unlabeled datasets using scikit-learn and scipy.
Deep Learning in Python
Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0.
Network Analysis in Python (Part 1)
This course will equip you with the skills to analyse, visualise, and make sense of networks using the NetworkX library.
Who Is It For?
Beginners with minimal notions of math and programming looking for a career in data science. Most notions will be explained along the way.
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29/month Unlimited access to all DataCamp courses.
About the Provider
DataCamp was created by a few Belgian enthusiasts and soon grew exponentially. It now has offices in Leuven, Belgium, and Cambridge, MA.
This course is taught by 12 instructors, experts either from DataCamp or from various other companies operating in the field of data science.