Skill Path: Data Science On-Ramp

In this skill path, learners who are new to data science will gain the fundamental skills — foundation in Python, using Jupyter notebooks to collaborate and create interactive visualizations, data manipulation and cleaning, plus more — and tools to build projects and work towards their first data science job.

Topics covered include:

• Programming in Python
• Anaconda & Jupyter Notebooks
• Forming and testing hypotheses about data
• Communicating insights to business leaders
• Data analysis with pandas
• Data visualization
• Data cleaning with pandas, Seaborn, and Matplotlib
• Finding data sets for your first independent projects
• Best practices for building projects, portfolios, and their online presence

Learners will also receive expert feedback on their portfolios so they can confidently start interviewing for data science roles.

By the end of this hands-on course, you’ll understand:

• How to read and write Python code
• How different parts of the technology stack work together
• Useful libraries for data science and machine learning
• How to open and work with a Jupyter notebook or IDE
• How to create pandas dataframes from various data sources
• Describe basic concepts of data visualization using Python
• Explain your data through visualization
• What constitutes data cleaning and why it is necessary
• Techniques on dealing with missing values and outliers
• best practices for a data science portfolio
• How do you present yourself (LinkedIn, certifications, personal site) to stand out?
• What are the recommended strategies while showcasing your portfolio?

And you’ll be able to:

• Work with pandas to rapidly slice and dice your data
• Import data into pandas, 
• Clean, process, and export your pandas dataframes
• Transform, reshape, and quantify your data
• Take raw inputs and sanitize them for more sophisticated tasks
• Strategize how to handle outliers, missing values, and bad data 
• Curate your projects and online presence to attract hiring managers
• Know where to find quality data sets to start your project 
• Evaluate data science portfolios
• Develop a portfolio that follows best practices
• Tailor the portfolio to get your dream data science job

This training is for you because…

• You’re new to data science.
• You want to learn Python and apply it to data science
• You want to better communicate about data
• You want to prepare for your first data science role.