Associate Data Scientist in 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 confidently pass the Associate Data Scientist in Python certification and thrive as a data scientist.

Python86hrs22 courses11 projectsStatement of Accomplishment

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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.

4 hours

Intermediate Python

Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.

4 hours

Investigating Netflix Movies

Apply the foundational Python skills you learned in Introduction to Python and Intermediate Python by manipulating and visualizing movie data.

2 hours

Data Manipulation with pandas

Learn how to import and clean data, calculate statistics, and create visualizations with pandas.

4 hours

Exploring NYC Public School Test Result Scores

Use data manipulation and summary statistics to analyze test scores across New York City's public schools!

2 hours

Joining Data with pandas

Learn to combine data from multiple tables by joining data together using pandas.

4 hours

Introduction to Statistics in Python

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.

4 hours

Introduction to Data Visualization with Matplotlib

Learn how to create, customize, and share data visualizations using Matplotlib.

4 hours

Introduction to Data Visualization with Seaborn

Learn how to create informative and attractive visualizations in Python using the Seaborn library.

4 hours

Visualizing the History of Nobel Prize Winners

Explore a dataset containing a century's worth of Nobel Laureates. Who won? Who got snubbed?

2 hours

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.

3 hours

Python Data Science Toolbox (Part 2)

Continue to build your modern Data Science skills by learning about iterators and list comprehensions.

4 hours

Data Manipulation with Python

Exploratory Data Analysis in Python

Learn how to explore, visualize, and extract insights from data using exploratory data analysis (EDA) in Python.

4 hours

Analyzing Crime in Los Angeles

Find out when and where crime is most likely to occur, along with the types of crimes commonly committed in LA.

2 hours

Working with Categorical Data in Python

Learn how to manipulate and visualize categorical data using pandas and seaborn.

4 hours

Customer Analytics: Preparing Data for Modeling

Apply your knowledge of data types and categorical data to prepare a big dataset for modeling!

2 hours

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.

3 hours

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.

3 hours

Cleaning Data in Python

Learn to diagnose and treat dirty data and develop the skills needed to transform your raw data into accurate insights!

4 hours

Exploring Airbnb Market Trends

Apply your importing and cleaning data and data manipulation skills to explore New York City Airbnb data.

2 hours

Working with Dates and Times in Python

Learn how to work with dates and times in Python.

4 hours

Importing & Cleaning Data with Python

Writing Functions in Python

Learn to use best practices to write maintainable, reusable, complex functions with good documentation.

4 hours

Python Programming

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.

4 hours

Modeling Car Insurance Claim Outcomes

Clean customer data and use logistic regression to predict whether people will make a claim on their car insurance!

2 hours

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.

4 hours

Hypothesis Testing in Python

Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

4 hours

Hypothesis Testing with Men's and Women's Soccer Matches

Perform a hypothesis test to determine if more goals are scored in women's soccer matches than men's!

2 hours

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!

4 hours

Predictive Modeling for Agriculture

Dive into agriculture using supervised machine learning and feature selection to aid farmers in crop cultivation and solve real-world problems.

2 hours

Unsupervised Learning in Python

Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.

4 hours

Clustering Antarctic Penguin Species

Arctic Penguin Exploration: Unraveling Clusters in the Icy Domain with K-means Clustering

2 hours

Machine Learning with Tree-Based Models in Python

In this course, you'll learn how to use tree-based models and ensembles for regression and classification using scikit-learn.

5 hours

Predicting Movie Rental Durations

Build a regression model for a DVD rental firm to predict rental duration. Evaluate models to recommend the best one.

2 hours

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Top reviews

Wilfrido O.

5 months

This career track has everything need for data science! I

Imre L.

7 months

OK.

Muhammad A.

9 months

I have taken the previous version of the course as well. I think that may be more alligned to theory, the newer version is more suitable for newbies. Overall, it's a good addition. However, the significane of the subject requires more and more practice on these topics so that a student can be master on these.

Aldo V.

9 days

Courses are great and give you a great follow through, what I think could help more is having a more complete exercise at the end of each course that requires you to code everything and not just fill the blank spaces

Maciej G.

22 days

Well created skill track, that took me round 2 years to finish. Good quality materials, test, task and perfect bright teachers.

"This career track has everything need for data science! I"

Wilfrido O.

"OK."

Imre L.

"I have taken the previous version of the course as well. I think that may be more alligned to theory, the newer version is more suitable for newbies. Overall, it's a good addition. However, the significane of the subject requires more and more practice on these topics so that a student can be master on these."

Muhammad A.

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Associate Data Scientist in Python

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Certification available

Instructors

Don’t just take our word for it

FAQs

Which jobs will benefit from this Track?

How will this Track prepare me for my career?

How long does it take to complete this Track?

What's the difference between a skill track and a career track?

What tasks will I learn in this Track?

What libraries will I use in this Track?

Join over .css-ou6dz6{color:#03ef62;}13,620,000 learners and start Associate Data Scientist in Python today!

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Training 2 or more people?

Join over 13,620,000 learners and start Associate Data Scientist in Python today!