Programming for Python Data Science: Principles to Practice Specialization

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

Instructors: Andrew D. Hilton +3 more

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.

    • Skills you'll gain

  •   Debugging
  •   Statistical Methods
  •   NumPy
  •   Algorithms
  •   Matplotlib
  •   Pandas (Python Package)
  •   Computational Thinking
  •   Data Analysis
  •   Object Oriented Programming (OOP)
  •   Predictive Modeling
  •   Data Cleansing
  •   Visualization (Computer Graphics)

    • Specialization - 5 course series

    Throughout this specialization, you’ll create programs to analyze real-world data and produce insights to the most important issues facing society (e.g., infant mortality, economic indices, and carbon emissions). You’ll learn a process to translate abstract problems into functional programs that will create reproducible analyses. Each course emphasizes discrete parts of a data scientist’s toolkit. All courses focus on practical applications, whether you’re debugging basic Python code in industry-standard libraries or optimizing and evaluating predictive models. By completing the programming exercises in this specialization, you’ll develop the analytical and technical skills necessary for completing a full data science pipeline– starting with a messy dataset and resulting in a publication-quality visualization.

    Starting with foundational computer science concepts, such as object-oriented programming and data organization using sets and dictionaries, you'll progress to more intricate data structures like arrays, vectors, and matrices. Hands-on practice with NumPy will equip you with essential skills to tackle big data challenges and solve data problems effectively. You'll write Python programs to manipulate and filter data, as well as create useful insights out of large datasets. By the end of the course, you'll be adept at summarizing datasets, such as calculating averages, minimums, and maximums. Additionally, you'll gain advanced skills in optimizing data analysis with vectorization and randomizing data. Throughout your learning journey, you'll use many kinds of data structures and analytic techniques for a variety of data science challenges , including mathematical operations, text file analysis, and image processing. Stepwise, guided assignments each week will reinforce your skills, enabling you to solve problems and draw data-driven conclusions independently. Prepare yourself for a rewarding career in data science by mastering NumPy and honing your programming prowess. Start this transformative learning experience today!

    Data Science with NumPy, Sets, and Dictionaries

    Pandas for Data Science

    Designing Larger Python Programs for Data Science

    Data Visualization and Modeling in Python

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