Duke University
Programming for Python Data Science: Principles to Practice Specialization
Duke University

Programming for Python Data Science: Principles to Practice Specialization

Harness the Potential of Python for Data Science. Optimize, analyze, and visualize data effectively

Andrew D. Hilton
Nick Eubank
Kyle Bradbury

Instructors: Andrew D. Hilton

Access provided by New York State Department of Labor

3,494 already enrolled

Get in-depth knowledge of a subject
4.1

(40 reviews)

Beginner level

Recommended experience

4 months
at 5 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.1

(40 reviews)

Beginner level

Recommended experience

4 months
at 5 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Leverage a Seven Step framework to create algorithms and programs.

  • Use NumPy and Pandas to manipulate, filter, and analyze data with arrays and matrices.

  • Utilize best practices for cleaning, manipulating, and optimizing data using Python.

  • Create classification models and publication quality visualizations with your datasets.

Details to know

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Taught in English
Recently updated!

January 2025

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Duke University
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Specialization - 5 course series

Python Programming Fundamentals

Course 123 hours4.0 (48 ratings)

What you'll learn

  • Utilize a Logical Seven Step framework to create algorithms and programs

  • Create useful test cases and efficiently debug Python code.

  • Master Python basics (conditionals, loops, mathematical operators, data types)

  • Develop a Python Program from scratch to solve a given data science problem.

Skills you'll gain

Category: Python Programming
Category: Algorithms
Category: Data Analysis
Category: Program Development
Category: Debugging
Category: Software Testing
Category: Computational Thinking
Category: Data Processing
Category: Microsoft Development Tools
Category: Programming Principles
Category: Computer Programming
Category: Data Manipulation
Category: Integrated Development Environments
Category: Scripting Languages
Category: Software Development

Data Science with NumPy, Sets, and Dictionaries

Course 230 hours3.4 (12 ratings)

What you'll learn

Skills you'll gain

Category: Object Oriented Programming (OOP)
Category: NumPy
Category: Data Structures
Category: Data Manipulation
Category: Python Programming
Category: Data Analysis
Category: Performance Tuning
Category: Data Science
Category: Algorithms
Category: Image Analysis
Category: Text Mining

Pandas for Data Science

Course 341 hours

What you'll learn

  • How and when to leverage the Pandas library for your data science projects

  • Best practices for cleaning, manipulating, and optimizing data with Pandas

Skills you'll gain

Category: Pandas (Python Package)
Category: Python Programming
Category: Debugging
Category: Data Cleansing
Category: Data Integration
Category: Data Import/Export
Category: Data Manipulation
Category: Data Analysis
Category: NumPy
Category: Query Languages
Category: Data Validation
Category: File Management
Category: Data Transformation

What you'll learn

  • How to plan program decomposition using top down design.

  • How to integrate discrete pieces of Python code into a larger, more functional, and complex program.

Skills you'll gain

Category: Debugging
Category: Simulations
Category: Test Case
Category: Object Oriented Programming (OOP)
Category: Python Programming
Category: Program Development
Category: Pandas (Python Package)
Category: Computer Programming
Category: Software Design
Category: Data Manipulation
Category: Data Structures
Category: Statistical Methods
Category: Integration Testing
Category: Data Science
Category: Computational Thinking

What you'll learn

  • Create professional visualizations for many kinds of data Utilize Classification algorithms to make predictions using a dataset

Skills you'll gain

Category: Predictive Modeling
Category: Machine Learning Algorithms
Category: Python Programming
Category: Data Science
Category: Regression Analysis
Category: Probability & Statistics
Category: Matplotlib
Category: Data Visualization Software
Category: Statistical Methods
Category: Statistical Inference
Category: Visualization (Computer Graphics)
Category: Pandas (Python Package)
Category: Data Cleansing
Category: Data Analysis

Instructors

Andrew D. Hilton
Duke University
19 Courses1,088,062 learners
Nick Eubank
Duke University
5 Courses21,650 learners

Offered by

Duke University

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