Syllabus
The Data Analytics Professional Certificate
The Data Analytics Professional Certificate is a self-paced, flexible program that can be completed in 9 months. You’ll be equipped with business and data analytics skills required for roles across a variety of companies and industries. The program will teach you how to frame business problems, wrangle data in spreadsheets, create data visualizations, and run data queries in SQL. You will also learn how to use Tableau software. This certificate is a Career Launch program, designed for employees with no prior experience. Expect to spend 10 hours or less a week, with individualized support along the way. Career Launch certificates 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
Understanding how to analyze data can help you improve operations and develop profitable businesses
This certificate will also prepare you to pursue a business analyst or data analyst career
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:

Statistics 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: Statistics for Analytics

This course will teach you to use statistical techniques to analyze data. You’ll complete projects using Google Sheets and Python.

 

Learning Outcomes:

  • Conduct statistical assessments using discrete and conditional probability.
  • Develop multiple linear regression models.
  • Run A/B tests to test data hypotheses and refine solutions.
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:

Statistics for Analytics

This course will teach you to use statistical techniques to analyze data. You’ll complete projects using Google Sheets and Python.

Learning Outcomes:

  • Conduct statistical assessments using discrete and conditional probability.
  • Develop multiple linear regression models.
  • Run A/B tests to test data hypotheses and refine solutions.
What You’ll Learn:
After completing this program, you’ll be ready to:

 

  • Frame business problems effectively
  • 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
  • Learn to visualize data using Tableau Desktop software
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 6 months.
  • Complete real business projects in an online platform and get individualized support and feedback from instructors.
  • Practice using data analytics and data visualization software directly in the learning platform. No separate downloads.
  • Explore the real work that project managers and data analysts do on the job and apply those skills to your own career.
  • Access individualized career coaching to help you get promoted and advance professionally.

FAQs

What is the schedule?

There are four courses which will be open for 8 weeks each with a 1-week grading period after each. You should expect to spend 10 hours per week getting through the coursework. Courses will open and close on a specific start and end date, after which you’ll no longer be able to access the course or submit projects for grading. 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-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 often 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. We’ve found that students who follow our suggested course schedule are much more likely to earn the certificate.

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. Comfort with high school level mathematics is recommended. In addition, students should have basic computer literacy skills including familiarity with Google Suite tools such as Google Docs and Google Slides.

What industry certifications will I be prepared for?

This certificate program aligns to the Tableau Desktop Specialist Certification Exam. While we recommend additional study beyond this program, you’ll gain a headstart in your preparation for this industry-leading certification.

What is Pathstream?

Pathstream is a provider of digital skills training based in Silicon Valley. We partner with leading tech companies and universities like Harvard, New York University (NYU) and Emory University to develop programs that prepare people for in-demand jobs.

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