Syllabus
Advanced Data Analytics with Python
The Advanced Data Analytics Professional Certificate with Python is designed to enhance the skills of people who regularly interact with and use data in their current role. You will learn critical analysis and visualization best practices and tools including Python, SQL and Tableau to clean and manipulate real data sets and share insights with business professionals. This certificate is designed for people with some prior experience analyzing data. It will provide in-demand skills AND result in college credits that can count towards a degree.
Why Data Analytics?
Data and business analytics skills are highly valued in nearly every industry
Python is a powerful programming language that can help you efficiently uncover new insights from data
Understanding how to analyze data can help you improve operations and develop profitable businesses
4 Courses | Hands-On Learning and Career Exploration
Course 1:
Business Analytics Fundamentals
Course 2:
SQL for Analytics
Course 3:
Data Visualization with Tableau
Course 4:
Python for Analytics
Course 1: Business Analytics Fundamentals
This course is designed to introduce you to the fundamentals of Business and Data Analytics. You will practice skills for data wrangling, data visualizations, descriptive statistics, exploratory data analysis, and data storytelling. The course culminates with a hands-on project in which you will perform an end-to-end exploratory data analysis (EDA). This course is designed for students with little or no background in business or analytics. Upon completion, you will be able to apply your new knowledge to make compelling business recommendations based on data. Watch your new insights come to life by making compelling data visualizations.
Learning Outcomes:
- Construct business framing applications for analytics problem-solving processes.
- Apply spreadsheet software to manipulate and prepare data for analysis.
- Communicate analysis insights to intended audiences, such as business stakeholders.
Course 2: SQL for Analytics
In this course, you will learn the fundamentals of SQL through a guided case study project, where you will act as a data analyst supporting the growth of the new company. You will build DDL (data definition language) and DML (data manipulation language) queries using MySQL workbench. You will assess the existing data infrastructure, apply appropriate changes to a database, and present insights to business stakeholders.
Learning Outcomes:
- Explain the role and structure of relational databases as they apply to data analytics.
- Extract meaningful insights from relational databases using Data Manipulation Language (DML).
- Design industry-standard relational database schemas using Data Definition Language (DDL).
- Revise database schema to meet criteria of normal forms (1NF, 2NF, & 3NF).
Course 3: Data Visualization with Tableau
In this course, you will learn the fundamentals of data visualization, including how to communicate insights from data. You will be learning in an online lab environment using real industry data sets and building directly in Tableau software embedded in the learning experience (no downloads required). You will create and design both static and dynamic tables, data visualizations, dashboards, and stories while incorporating visual design best practices. You will also connect multiple external data sources and optimize large data to efficiently wrangle and analyze industry data.
Learning Outcomes:
- Learn to use Tableau Software to visualize data.
- Build interactive tables by connecting, preparing, and customizing data in Tableau.
- Create data visualizations, dashboards, and Tableau Stories, to communicate insights to business stakeholders.
- Apply Tableau performance optimization to improve speed when working with large datasets.
Course 4: Python for Analytics
In this course, you’ll be introduced to the fundamentals of programming in Python. You’ll learn to create Python scripts in an interactive development environment and combine foundational Python with functionality within data-specific libraries. You’ll use Python to explore, wrangle, visualize, statistically infer, and present data.
Learning Outcomes:
- Create and use a custom statistical and data wrangling library with Python.
- Apply refactoring techniques to produce efficient and readable code.
- Perform an end-to-end analysis on real-world data using Python packages including NumPy, pandas, and matplotlib.
- Organize and refine the code and text within a Jupyter notebook to present findings to technical and non-technical stakeholders.
4 Courses | Hands-On Learning and Career Exploration
Course 1:
Business Analytics Fundamentals
This course is designed to introduce you to the fundamentals of Business and Data Analytics. You will practice skills for data wrangling, data visualizations, descriptive statistics, exploratory data analysis, and data storytelling. The course culminates with a hands-on project in which you will perform an end-to-end exploratory data analysis (EDA). This course is designed for students with little or no background in business or analytics. Upon completion, you will be able to apply your new knowledge to make compelling business recommendations based on data. Watch your new insights come to life by making compelling data visualizations.
Learning Outcomes:
- Construct business framing applications for analytics problem-solving processes.
- Apply spreadsheet software to manipulate and prepare data for analysis.
- Communicate analysis insights to intended audiences, such as business stakeholders.
Course 2:
SQL for Analytics
In this course, you will learn the fundamentals of SQL through a guided case study project, where you will act as a data analyst supporting the growth of the new company. You will build DDL (data definition language) and DML (data manipulation language) queries using MySQL workbench. You will assess the existing data infrastructure, apply appropriate changes to a database, and present insights to business stakeholders.
Learning Outcomes:
- Explain the role and structure of relational databases as they apply to data analytics.
- Extract meaningful insights from relational databases using Data Manipulation Language (DML).
- Design industry-standard relational database schemas using Data Definition Language (DDL).
- Revise database schema to meet criteria of normal forms (1NF, 2NF, & 3NF).
Course 3:
Data Visualization with Tableau
In this course, you will learn the fundamentals of data visualization, including how to communicate insights from data. You will be learning in an online lab environment using real industry data sets and building directly in Tableau software embedded in the learning experience (no downloads required). You will create and design both static and dynamic tables, data visualizations, dashboards, and stories while incorporating visual design best practices. You will also connect multiple external data sources and optimize large data to efficiently wrangle and analyze industry data.
Learning Outcomes:
- Learn to use Tableau Software to visualize data.
- Build interactive tables by connecting, preparing, and customizing data in Tableau.
- Create data visualizations, dashboards, and Tableau Stories, to communicate insights to business stakeholders.
- Apply Tableau performance optimization to improve speed when working with large datasets.
Course 4:
Python for Analytics
In this course, you’ll be introduced to the fundamentals of programming in Python. You’ll learn to create Python scripts in an interactive development environment and combine foundational Python with functionality within data-specific libraries. You’ll use Python to explore, wrangle, visualize, statistically infer, and present data.
Learning Outcomes:
- Create and use a custom statistical and data wrangling library with Python.
- Apply refactoring techniques to produce efficient and readable code.
- Perform an end-to-end analysis on real-world data using Python packages including NumPy, pandas, and matplotlib.
- Organize and refine the code and text within a Jupyter notebook to present findings to technical and non-technical stakeholders.
What You’ll Learn:
After completing this program, you’ll be ready to:
- Identify insights from data using exploratory data analysis and communicate insights to business stakeholders
- Learn SQL and design industry-standard relational database schemas
- Perform inferential data analysis and construct a simple predictive model
- Visualize data using Tableau software
- Perform an end-to-end analysis on real-world data using Python packages including NumPy, pandas, and matplotlib
Learning Experience
- No required times to log in. Complete lessons at times during the week that work for you. Keep up with deadlines to stay on track and complete in 10 months.
- Complete real business projects in an online platform and get individualized support and feedback from instructors.
- Practice using project management, spreadsheet, and other types of software directly in the learning platform. No separate downloads.
- Explore the real work that data analysts do on the job and apply those skills to your own career.
FAQs
What is the schedule?
There are four required courses to complete this certificate. The first three will be open for 8 weeks each with a 1-week grading period after, and the fourth course will be open for 11 weeks with a 1-week grading period after. You should expect to spend 10-12 hours per week completing your coursework. The program is flexibly-paced, meaning you can move as quickly or slowly as you’d like through each course, as long as you complete all sections and projects during the 8 or 11 week course period. We provide a suggested course schedule to help pace yourself through each course. Students who follow this schedule are more likely to earn the certificate and get more out of the course by spreading out their workload, and our instructors provide weekly nudges to keep you on track. As long as you submit all projects by the course end date, you can progress through the course at whatever pace works best for you! For example, you might do all your work over the weekend or space it out throughout the week.
Can I work full-time while enrolled in this program?
Yes, the entire course experience is online and can be completed on your own schedule as long as you work towards the deadlines set in each course. There are no set times or classes when you need to log in. Our courses are designed for working professionals, students, and parents!
What prerequisites do I need?
Students must have a high school degree prior to taking this program. No prior experience is required.
What is Pathstream?
Pathstream is a provider of digital skills training based in Silicon Valley. We partner with leading tech companies and universities to develop programs that prepare people for in-demand jobs.