Data Science Foundations Specialization

Unlock Academic & Career Success with Data Science. Build the foundational knowledge and hands-on skills you need to forge new career opportunities, with no technical experience required.

Instructors: Romeo Kienzler +7 more

What you'll learn

  •   Foundational knowledge and practical understanding of data science that unlocks academic and career opportunities
  •   Basic hands-on skills in Python, R, SQL, and tools like GitHub and Jupyter Notebooks, including their essential features and uses in data science
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  •   Foundational data science processes, including data collection, simple model building, and algorithm concepts using flowcharts and pseudocode.
  •   Basic data analysis with Python, using libraries like Pandas and Numpy, creating simple dashboards, and working with clustering algorithms.

    • Skills you'll gain

  •   Data Mining
  •   Jupyter
  •   Pseudocode
  •   Data Analysis Software
  •   Data Collection
  •   Algorithms
  •   Unsupervised Learning
  •   Probability & Statistics
  •   Big Data
  •   Machine Learning Algorithms
  •   Dashboard
  •   Pandas (Python Package)

    • Specialization - 8 course series

    There are two Capstone projects that draw together the material across the Data Science Foundations specialization to enable you to apply what you have learned. In one project, students will tackle a prediction problem: forecasting the number of bicycles that will be rented on a given day. Using historical data, students will consider factors such as weather, the day of the week, and other relevant variables to accurately predict daily bicycle rentals. This will help ensure that the bicycle rental service is prepared with the appropriate number of bicycles each day. Students will learn specifically about data acquisition, linear regression, and correlation. In the other project, students will predict if the Falcon 9 rocket's first stage will land successfully and determine the cost of a launch. In doing so, students will apply skills to perform data collection, data wrangling, exploratory data analysis, data visualization model development, and model evaluation.

    What is Data Science?

    Tools for Data Science

    Problems, Algorithms and Flowcharts

    Python for Data Science, AI & Development

    Statistics and Clustering in Python

    Data Science Project Capstone: Predicting Bicycle Rental

    Python Project for Data Science

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