LEARNING PATH
LEARNING PATH
Python for Data Analytics
Python for Data Analytics
This path is for BI Analysts or Data Scientists looking to master Python's most powerful tools for data analysis and visualization, including Pandas, Matplotlib, Seaborn, Plotly and Dash.
This path is for BI Analysts or Data Scientists looking to master Python's most powerful tools for data analysis and visualization, including Pandas, Matplotlib, Seaborn, Plotly and Dash.
certificate available
76 hours
4 courses
3 guided projects
Overview
This path is for BI analysts or data scientists looking to build job-ready Python skills and master the most popular libraries for data analysis and visualization.
We'll start by mastering the core building blocks of Python for analytics, including data types, properties, and foundational tools like variables, numeric and string operators, conditional logic, loops and functions.
Next we'll dive into NumPy & Pandas, two of the most popular Python packages for data analysis. We'll introduce arrays and array properties, common operations like indexing, slicing, filtering and sorting, and powerful methods for exploring, analyzing, aggregating and transforming dataframes.
From there we'll explore data visualization methods using Matplotlib & Seaborn. We'll introduce data visualization frameworks and best practices, review tools and techniques for building and customizing basic charts, then explore advanced formatting options and custom visuals.
Last but not least we'll use Plotly & Dash to build and deploy interactive visuals, dashboards, and web applications.
This path is designed to help you learn job-ready skills, solve real business problems, and build a project portfolio to showcase your skills to peers and employers.
Skills You'll Learn
Data Prep
Data Analysis
Data Visualization
Who Should Take This Path?
Data Analysts or BI professionals looking to build expert-level Python skills
Aspiring data scientists who want to learn Python for data analysis and visualization
Students looking for a hands-on, project-based learning experience
Path Requirements
Jupyter Notebooks (free download, we'll walk through the install)
No advance preparation is required (basic familiarity with programming is a plus, but not a prerequisite)
Meet Your Instructors
Chris Bruehl
Analytics Engineer & Lead Python Instructor
Chris is a Python expert, certified Statistical Business Analyst, and seasoned Data Scientist, having held senior-level roles at large insurance firms and financial service companies. He earned a Masters in Analytics at NC State's Institute for Advanced Analytics, where he founded the IAA Python Programming club.
Overview
This path is for BI analysts or data scientists looking to build job-ready Python skills and master the most popular libraries for data analysis and visualization.
We'll start by mastering the core building blocks of Python for analytics, including data types, properties, and foundational tools like variables, numeric and string operators, conditional logic, loops and functions.
Next we'll dive into NumPy & Pandas, two of the most popular Python packages for data analysis. We'll introduce arrays and array properties, common operations like indexing, slicing, filtering and sorting, and powerful methods for exploring, analyzing, aggregating and transforming dataframes.
From there we'll explore data visualization methods using Matplotlib & Seaborn. We'll introduce data visualization frameworks and best practices, review tools and techniques for building and customizing basic charts, then explore advanced formatting options and custom visuals.
Last but not least we'll use Plotly & Dash to build and deploy interactive visuals, dashboards, and web applications.
This path is designed to help you learn job-ready skills, solve real business problems, and build a project portfolio to showcase your skills to peers and employers.
Skills You'll Learn
Data Prep
Data Analysis
Data Visualization
Who Should Take This Path?
Data Analysts or BI professionals looking to build expert-level Python skills
Aspiring data scientists who want to learn Python for data analysis and visualization
Students looking for a hands-on, project-based learning experience
Path Requirements
Jupyter Notebooks (free download, we'll walk through the install)
No advance preparation is required (basic familiarity with programming is a plus, but not a prerequisite)
Meet Your Instructors
Chris Bruehl
Analytics Engineer & Lead Python Instructor
Chris is a Python expert, certified Statistical Business Analyst, and seasoned Data Scientist, having held senior-level roles at large insurance firms and financial service companies. He earned a Masters in Analytics at NC State's Institute for Advanced Analytics, where he founded the IAA Python Programming club.
Overview
This path is for BI analysts or data scientists looking to build job-ready Python skills and master the most popular libraries for data analysis and visualization.
We'll start by mastering the core building blocks of Python for analytics, including data types, properties, and foundational tools like variables, numeric and string operators, conditional logic, loops and functions.
Next we'll dive into NumPy & Pandas, two of the most popular Python packages for data analysis. We'll introduce arrays and array properties, common operations like indexing, slicing, filtering and sorting, and powerful methods for exploring, analyzing, aggregating and transforming dataframes.
From there we'll explore data visualization methods using Matplotlib & Seaborn. We'll introduce data visualization frameworks and best practices, review tools and techniques for building and customizing basic charts, then explore advanced formatting options and custom visuals.
Last but not least we'll use Plotly & Dash to build and deploy interactive visuals, dashboards, and web applications.
This path is designed to help you learn job-ready skills, solve real business problems, and build a project portfolio to showcase your skills to peers and employers.
Skills You'll Learn
Data Prep
Data Analysis
Data Visualization
Who Should Take This Path?
Data Analysts or BI professionals looking to build expert-level Python skills
Aspiring data scientists who want to learn Python for data analysis and visualization
Students looking for a hands-on, project-based learning experience
Path Requirements
Jupyter Notebooks (free download, we'll walk through the install)
No advance preparation is required (basic familiarity with programming is a plus, but not a prerequisite)
Meet Your Instructors
Chris Bruehl
Analytics Engineer & Lead Python Instructor
Chris is a Python expert, certified Statistical Business Analyst, and seasoned Data Scientist, having held senior-level roles at large insurance firms and financial service companies. He earned a Masters in Analytics at NC State's Institute for Advanced Analytics, where he founded the IAA Python Programming club.
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