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Python for Data Analytics

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

opened black laptop computer
opened black laptop computer
opened black laptop computer

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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FOR INDIVIDUALS

Master data & AI skills

Build data & AI skills to launch or accelerate your career (start for free, no credit card required).

FOR COMPANIES & TEAMS

Transform your workforce

Assess your team's data & AI skills and follow personalized learning plans to close the gaps.

FOR INDIVIDUALS

Master data & AI skills

Build data & AI skills to launch or accelerate your career (start for free, no credit card required).

FOR COMPANIES & TEAMS

Transform your workforce

Assess your team's data & AI skills and follow personalized learning plans to close the gaps.

FOR INDIVIDUALS

Master data & AI skills

Build data & AI skills to launch or accelerate your career (start for free, no credit card required).

FOR COMPANIES & TEAMS

Transform your workforce

Assess your team's data & AI skills and follow personalized learning plans to close the gaps.