Data Scientist with Python

Career track

Data Scientist with Python

Gain the career-building Python skills you need to succeed as a data scientist. No prior coding experience required. 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. Through interactive exercises, you'll get hands-on with some of the most popular Python libraries, including pandas, NumPy, Matplotlib, and many more. You'll then work with real-world datasets to learn the statistical and machine learning techniques you need to train decision trees and use natural language processing (NLP). Start this track, grow your Python skills, and begin your journey to becoming a confident data scientist.

Python

Clock: 88 hours Learn: 23 Courses Apply: 6 Projects

1. Introduction to Python (https://www.datacamp.com/courses/intro-to-python-for-data-science)

Master the basics of data analysis in Python. Expand your skillset by learning scientific computing with NumPy.

4 hours

2. Intermediate Python (https://www.datacamp.com/courses/intermediate-python)

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

4 hours

3. Investigating Netflix Movies and Guest Stars in The Office (https://www.datacamp.com/projects/1237)

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

2 hours

4. Data Manipulation with pandas (https://www.datacamp.com/courses/data-manipulation-with-pandas)

Use the world’s most popular Python data science package to manipulate data and calculate summary statistics.

4 hours

5. The Android App Market on Google Play (https://www.datacamp.com/projects/619)

Load, clean, and visualize scraped Google Play Store data to gain insights into the Android app market.

2 hours

6. Joining Data with pandas (https://www.datacamp.com/courses/joining-data-with-pandas)

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

4 hours

7. The GitHub History of the Scala Language (https://www.datacamp.com/projects/163)

Find the true Scala experts by exploring its development history in Git and GitHub.

2 hours

8. Introduction to Data Visualization with Matplotlib (https://www.datacamp.com/courses/introduction-to-data-visualization-with-matplotlib)

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

4 hours

9. Introduction to Data Visualization with Seaborn (https://www.datacamp.com/courses/introduction-to-data-visualization-with-seaborn)

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

4 hours

10. Python Data Science Toolbox (Part 1) (https://www.datacamp.com/courses/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

11. Python Data Science Toolbox (Part 2) (https://www.datacamp.com/courses/python-data-science-toolbox-part-2)

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

4 hours

12. Intermediate Data Visualization with Seaborn (https://www.datacamp.com/courses/intermediate-data-visualization-with-seaborn)

Use Seaborn's sophisticated visualization tools to make beautiful, informative visualizations with ease.

4 hours

13. A Visual History of Nobel Prize Winners (https://www.datacamp.com/projects/441)

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

2 hours

14. Data Manipulation with Python](https://www.datacamp.com/signal)

15. Introduction to Importing Data in Python (https://www.datacamp.com/courses/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

16. Intermediate Importing Data in Python (https://www.datacamp.com/courses/intermediate-importing-data-in-python)

Improve your Python data importing skills and learn to work with web and API data.

2 hours

17. Cleaning Data in Python (https://www.datacamp.com/courses/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

18. Working with Dates and Times in Python (https://www.datacamp.com/courses/working-with-dates-and-times-in-python)

Learn how to work with dates and times in Python.

4 hours

19. Importing & Cleaning Data with Python](https://www.datacamp.com/signal)

20. Writing Functions in Python (https://www.datacamp.com/courses/writing-functions-in-python)

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

4 hours

21. Python Programming](https://www.datacamp.com/signal)

22. Exploratory Data Analysis in Python (https://www.datacamp.com/courses/exploratory-data-analysis-in-python)

Learn how to explore, visualize, and extract insights from data.

4 hours

23. Analyzing Police Activity with pandas (https://www.datacamp.com/courses/analyzing-police-activity-with-pandas)

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

4 hours

24. Statistical Thinking in Python (Part 1) (https://www.datacamp.com/courses/statistical-thinking-in-python-part-1)

Build the foundation you need to think statistically and to speak the language of your data.

3 hours

25. Statistical Thinking in Python (Part 2) (https://www.datacamp.com/courses/statistical-thinking-in-python-part-2)

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

4 hours

26. Dr. Semmelweis and the Discovery of Handwashing (https://www.datacamp.com/projects/20)

Reanalyse the data behind one of the most important discoveries of modern medicine: handwashing.

2 hours

27. Supervised Learning with scikit-learn (https://www.datacamp.com/courses/supervised-learning-with-scikit-learn)

Learn how to build and tune predictive models and evaluate how well they'll perform on unseen data.

4 hours

28. Predicting Credit Card Approvals (https://www.datacamp.com/projects/558)

Build a machine learning model to predict if a credit card application will get approved.

2 hours

29. Unsupervised Learning in Python (https://www.datacamp.com/courses/unsupervised-learning-in-python)

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

4 hours

30. Machine Learning with Tree-Based Models in Python (https://www.datacamp.com/courses/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

31. Case Study: School Budgeting with Machine Learning in Python (https://www.datacamp.com/courses/case-study-school-budgeting-with-machine-learning-in-python)

Learn how to build a model to automatically classify items in a school budget.

4 hours

32. Cluster Analysis in Python (https://www.datacamp.com/courses/cluster-analysis-in-python)

In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.

4 hours

Instructors

[
Hugo Bowne-AndersonData Scientist at DataCamp
(https://www.datacamp.com/instructors/hugobowne)
[
Justin Saddlemyer
(https://www.datacamp.com/instructors/jsaddlemyer)
[
Richie CottonCurriculum Architect at DataCamp
(https://www.datacamp.com/instructors/richie)
[
Maggie MatsuiCurriculum Manager at DataCamp
(https://www.datacamp.com/instructors/maggiematsui) See all instructors

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Last updated 4 years ago

hashtagData Scientist with Python

hashtag1. Introduction to Python (https://www.datacamp.com/courses/intro-to-python-for-data-sciencearrow-up-right)

hashtag2. Intermediate Python (https://www.datacamp.com/courses/intermediate-pythonarrow-up-right)

hashtag3. Investigating Netflix Movies and Guest Stars in The Office (https://www.datacamp.com/projects/1237arrow-up-right)

hashtag4. Data Manipulation with pandas (https://www.datacamp.com/courses/data-manipulation-with-pandasarrow-up-right)

hashtag5. The Android App Market on Google Play (https://www.datacamp.com/projects/619arrow-up-right)

hashtag6. Joining Data with pandas (https://www.datacamp.com/courses/joining-data-with-pandasarrow-up-right)

hashtag7. The GitHub History of the Scala Language (https://www.datacamp.com/projects/163arrow-up-right)

hashtag8. Introduction to Data Visualization with Matplotlib (https://www.datacamp.com/courses/introduction-to-data-visualization-with-matplotlibarrow-up-right)

hashtag9. Introduction to Data Visualization with Seaborn (https://www.datacamp.com/courses/introduction-to-data-visualization-with-seabornarrow-up-right)

hashtag10. Python Data Science Toolbox (Part 1) (https://www.datacamp.com/courses/python-data-science-toolbox-part-1arrow-up-right)

hashtag11. Python Data Science Toolbox (Part 2) (https://www.datacamp.com/courses/python-data-science-toolbox-part-2arrow-up-right)

hashtag12. Intermediate Data Visualization with Seaborn (https://www.datacamp.com/courses/intermediate-data-visualization-with-seabornarrow-up-right)

hashtag13. A Visual History of Nobel Prize Winners (https://www.datacamp.com/projects/441arrow-up-right)

hashtag14. Data Manipulation with Python](https://www.datacamp.com/signalarrow-up-right)

hashtag15. Introduction to Importing Data in Python (https://www.datacamp.com/courses/introduction-to-importing-data-in-pythonarrow-up-right)

hashtag16. Intermediate Importing Data in Python (https://www.datacamp.com/courses/intermediate-importing-data-in-pythonarrow-up-right)

hashtag17. Cleaning Data in Python (https://www.datacamp.com/courses/cleaning-data-in-pythonarrow-up-right)

hashtag18. Working with Dates and Times in Python (https://www.datacamp.com/courses/working-with-dates-and-times-in-pythonarrow-up-right)

hashtag19. Importing & Cleaning Data with Python](https://www.datacamp.com/signalarrow-up-right)

hashtag20. Writing Functions in Python (https://www.datacamp.com/courses/writing-functions-in-pythonarrow-up-right)

hashtag21. Python Programming](https://www.datacamp.com/signalarrow-up-right)

hashtag22. Exploratory Data Analysis in Python (https://www.datacamp.com/courses/exploratory-data-analysis-in-pythonarrow-up-right)

hashtag23. Analyzing Police Activity with pandas (https://www.datacamp.com/courses/analyzing-police-activity-with-pandasarrow-up-right)

hashtag24. Statistical Thinking in Python (Part 1) (https://www.datacamp.com/courses/statistical-thinking-in-python-part-1arrow-up-right)

hashtag25. Statistical Thinking in Python (Part 2) (https://www.datacamp.com/courses/statistical-thinking-in-python-part-2arrow-up-right)

hashtag26. Dr. Semmelweis and the Discovery of Handwashing (https://www.datacamp.com/projects/20arrow-up-right)

hashtag27. Supervised Learning with scikit-learn (https://www.datacamp.com/courses/supervised-learning-with-scikit-learnarrow-up-right)

hashtag28. Predicting Credit Card Approvals (https://www.datacamp.com/projects/558arrow-up-right)

hashtag29. Unsupervised Learning in Python (https://www.datacamp.com/courses/unsupervised-learning-in-pythonarrow-up-right)

hashtag30. Machine Learning with Tree-Based Models in Python (https://www.datacamp.com/courses/machine-learning-with-tree-based-models-in-pythonarrow-up-right)

hashtag31. Case Study: School Budgeting with Machine Learning in Python (https://www.datacamp.com/courses/case-study-school-budgeting-with-machine-learning-in-pythonarrow-up-right)

hashtag32. Cluster Analysis in Python (https://www.datacamp.com/courses/cluster-analysis-in-pythonarrow-up-right)

hashtagInstructors