In this path, you’ll gain the fundamental skills to begin cleaning data, using the powerful tools offered by Python such as identifying and removing inaccurate records from a dataset. You’ll learn how to manipulate, analyze, and visualize data using premier Python libraries such as Pandas and Numpy.
Best of all, you’ll learn by doing — you’ll write code and get feedback directly in the browser. You’ll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview.
- Cleaning and visualizing data
- Programming with Python to manipulate data
- Working with missing data
Part 1: Introduction to Python [5 courses]
Introduction to Python Programming 3hObjectives
- Write computer programs using Python
- Save values using variables
- Process numerical data and text data
- Create lists using Python
For Loops and Conditional Statements in Python 5hObjectives
- Repeat a process using a for loop
- Employ if, else, and elif statements
- Employ logical operators and comparison operators
- Employ Jupyter Notebook
Dictionaries, Frequency Tables, and Functions in Python 4hObjectives
- Create Python dictionaries
- Build frequency tables using dictionaries
- Write Python functions
- Debug functions
Python Functions and Jupyter Notebook 5hObjectives
- Define function arguments
- Write functions that return multiple variables
- Employ Jupyter notebook
- Build a portfolio project
Intermediate Python for Data Science 8hObjectives
- Clean and analyze text data
- Define object-oriented programming in Python
- Process dates and times
Part 2: Intermediate Python and Pandas [2 courses]
Introduction to Pandas and NumPy for Data Analysis 13hObjectives
- Improve your workflow using vectorized operations
- Select data by value using Boolean indexing
- Analyze data using pandas and NumPy
Introduction to Data Visualization in Python 8hObjectives
- Visualize time series data with line plots
- Define correlations and visualize them with scatter plots
- Visualize frequency distributions with bar plots and histograms
- Improve your exploratory data visualization workflow using pandas
- Visualize multiple variables using Seaborn's relational plots
Part 3: Data Cleaning in Python [3 courses]
Data Cleaning and Analysis in Python 11hObjectives
- Employ data aggregation techniques
- Combine datasets
- Transform and reshape data
- Clean strings and resolve missing data
Advanced Data Cleaning in Python 9hObjectives
- Clean and manipulate text data using regular expressions
- Employ lambda functions and list comprehension with pandas
- Resolve missing data
Data Cleaning Project Walkthrough 7hObjectives
- Complete a data cleaning project from start to finish
- Improve your data cleaning skills
The Dataquest guarantee
Dataquest has helped thousands of people start new careers in data. If you put in the work and follow our path, you’ll master data skills and grow your career.
We believe so strongly in our paths that we offer a full satisfaction guarantee. If you complete a career path on Dataquest and aren’t satisfied with your outcome, we’ll give you a refund.
Master skills faster with Dataquest
Go from zero to job-ready
Learn exactly what you need to achieve your goal. Don’t waste time on unrelated lessons.
Build your project portfolio
Build confidence with our in-depth projects, and show off your data skills.
Challenge yourself with exercises
Work with real data from day one with interactive lessons and hands-on exercises.
Showcase your path certification
Impress employers by completing a capstone project and certifying it with an expert review.
Projects in this path
Guided Project: Prison Break
Learn the basics of Jupyter Notebook by analyzing a dataset on helicopter prison escapes
Project: Learn and Install Jupyter Notebook
Learn the basics of Jupyter Notebook
Guided Project: Profitable App Profiles for the App Store and Google Play Markets
Learn to combine the skills you learned in this course to perform practical data analysis.
Guided Project: Exploring Hacker News Posts
Practice using loops, cleaning strings, and working with dates in Python.
Guided Project: Exploring eBay Car Sales Data
Practice data cleaning and data exploration using pandas