Data Scientist with Python
Learn Python for data science and gain the career-building skills you need to succeed as a data scientist, from data manipulation to machine learning! In this track, you’ll learn how this versatile language allows you to import, clean, manipulate, and visualize data—all integral skills for any aspiring data professional or researcher. Starting with the Python essentials for data science, you’ll work through interactive exercises that test your abilities. You’ll get hands-on with some of the most popular Python libraries for data science, including pandas, Seaborn, Matplotlib, scikit-learn, and many more. As you progress, you’ll work with real-world datasets to learn the statistical and machine learning techniques you need to perform hypothesis testing and build predictive models. You’ll also get an introduction to supervised learning with scikit-learn and apply your skills to various projects. Start this track, grow your data science skills, and begin your journey to becoming a confident data scientist with Python.
Python90 hours23 Courses6 Projects
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Introduction to Python
Master the basics of data analysis with Python in just four hours. This online course will introduce the Python interface and explore popular packages.
Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.
Investigating Netflix Movies and Guest Stars in The Office
Apply the foundational Python skills you learned in Introduction to Python and Intermediate Python by manipulating and visualizing movie and TV data.
Data Manipulation with pandas
Learn how to import and clean data, calculate statistics, and create visualizations with pandas.
Joining Data with pandas
Learn to combine data from multiple tables by joining data together using pandas.
Introduction to Statistics in Python
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.
What and Where are the World's Oldest Businesses
Use joining techniques to discover the oldest businesses in the world.
Introduction to Data Visualization with Matplotlib
Learn how to create, customize, and share data visualizations using Matplotlib.
Introduction to Data Visualization with Seaborn
Learn how to create informative and attractive visualizations in Python using the Seaborn library.
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.
The Android App Market on Google Play
Load, clean, and visualize scraped Google Play Store data to gain insights into the Android app market.
Python Data Science Toolbox (Part 2)
Continue to build your modern Data Science skills by learning about iterators and list comprehensions.
Intermediate Data Visualization with Seaborn
Use Seaborn's sophisticated visualization tools to make beautiful, informative visualizations with ease.
A Visual History of Nobel Prize Winners
Explore a dataset from Kaggle containing a century's worth of Nobel Laureates. Who won? Who got snubbed?
Exploratory Data Analysis in Python
Learn how to explore, visualize, and extract insights from data using exploratory data analysis (EDA) in Python.
Working with Categorical Data in Python
Learn how to manipulate and visualize categorical data using pandas and seaborn.
Data Communication Concepts
No one enjoys looking at spreadsheets! Bring your data to life. Improve your presentation and learn how to translate technical data into actionable insights.
Introduction to Importing Data in Python
Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.
Cleaning Data in Python
Learn to diagnose and treat dirty data and develop the skills needed to transform your raw data into accurate insights!
Writing Functions in Python
Learn to use best practices to write maintainable, reusable, complex functions with good documentation.
Introduction to Regression with statsmodels in Python
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis with statsmodels in Python.
Sampling in Python
Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.
Hypothesis Testing in Python
Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.
Dr. Semmelweis and the Discovery of Handwashing
Reanalyse the data behind one of the most important discoveries of modern medicine: handwashing.
Supervised Learning with scikit-learn
Grow your machine learning skills with scikit-learn in Python. Use real-world datasets in this interactive course and learn how to make powerful predictions!
Predicting Credit Card Approvals
Build a machine learning model to predict if a credit card application will get approved.
Unsupervised Learning in Python
Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.
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