What background knowledge is necessary?

No background knowledge is necessary. This Professional Certificate is designed for those new to data analysis, but is valuable for anyone looking to enhance their data analytics skills.

Is this course really 100% online? Do I need to attend any classes in person?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Certificate, you’re automatically subscribed to the full Certificate. Visit your learner dashboard to track your progress.

Meta Data Analyst with GenAI Professional Certificate

Launch your career in data analytics. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from Meta in 5 months or less. No degree or prior experience required.

Instructors: Brandon Larkin

Included with Coursera Plus

Learn more

5 course series

Earn a career credential that demonstrates your expertise

4.7

(862 reviews)

Beginner level

Recommended experience

5 months at 10 hours a week

Flexible schedule

Earn a career credential

Share your expertise with employers

5 course series

Earn a career credential that demonstrates your expertise

4.7

(862 reviews)

Beginner level

Recommended experience

5 months at 10 hours a week

Flexible schedule

Earn a career credential

Share your expertise with employers

What you'll learn

Collect, clean, sort, evaluate, and visualize data
Apply the OSEMN, framework to guide the data analysis process, ensuring a comprehensive and structured approach to deriving actionable insights
Use statistical analysis, including hypothesis testing, regression analysis, and more, to make data-driven decisions
Develop an understanding of the foundational principles of effective data management and usability of data assets within organizational context

Overview

Prepare for a career in the high-growth field of data analytics. In this program, you’ll build in-demand technical skills like Python, Statistics, and SQL in spreadsheets to get job-ready in 5 months or less, no prior experience needed. You'll also have the option to learn how generative AI tools and techniques are used in data analytics.

Data analysis involves collecting, processing, and analyzing data to extract insights that can inform decision-making and strategy across an organization.

In this program, you’ll learn basic data analysis principles, how data informs decisions, and how to apply the OSEMN framework to approach common analytics questions. You’ll also learn how to use essential tools like SQL, Python, and Tableau to collect, connect, visualize, and analyze relevant data.

You’ll learn how to apply common statistical methods to writing hypotheses through project scenarios to gain practical experience with designing experiments and analyzing results.

When you complete this full program, you’ll have a portfolio of hands-on projects and a Professional Certificate from Meta to showcase your expertise.

What’s included

Shareable certificate

Add to your LinkedIn profile

Taught in English

108 practice exercises

Professional Certificate - 5 course series

Throughout the program, you’ll get to practice your new data analysis skills through hands-on projects including:

Identifying data sources
Using spreadsheets to clean and filter data
Using Python to sort and explore data
Using Tableau to visualize results
Using statistical analyses

By the end, you’ll have a professional portfolio that you can show to prospective employers or utilize for your own business.

Introduction to Data Analytics

Course 117 hours4.8 (988 ratings)View course

What you'll learn

Apply the data analysis process OSEMN to marketing data
Compare and contrast various data formats and their applications across different scenarios
Identify data gaps and articulate the strengths and weaknesses of collected data

Skills you'll gain

Exploratory Data Analysis, Data Storytelling, Data Collection, Data Cleansing, Key Performance Indicators (KPIs), Data Analysis, Data Management, Data Visualization, Business Analysis, Data Literacy, Analytical Skills, Data Quality, Analytics, Data Manipulation, Marketing, Business Metrics, Data Modeling, and Generative AI

Data Analysis with Spreadsheets and SQL

Course 226 hours4.6 (267 ratings)View course

What you'll learn

Clean data with spreadsheets and use common spreadsheet formulas to calculate summary statistics
Write foundational SQL statements and queries to extract data in spreadsheets
Create charts in Google Sheets and use Tableau to visualize data and use dashboards to create data visualizations

Skills you'll gain

Google Sheets, Tableau Software, Data Visualization Software, Data Manipulation, Spreadsheet Software, SQL, Dashboard, Correlation Analysis, Data Storytelling, Pivot Tables And Charts, Exploratory Data Analysis, Statistical Analysis, Data Analysis, Data Cleansing, Marketing Analytics, Data Visualization, and Descriptive Statistics

Python Data Analytics

Course 322 hours4.3 (232 ratings)View course

What you'll learn

Sort, query, and structure data in Pandas, the Python library
Describe how to model and interpret data using Python
Create basic data visualizations with Python libraries

Skills you'll gain

Data Manipulation, Pandas (Python Package), Exploratory Data Analysis, Data Visualization, Matplotlib, Data Cleansing, Programming Principles, Data Visualization Software, Python Programming, Jupyter, Scripting Languages, Data Modeling, Data Analysis, and Scripting

Statistics Foundations

Course 421 hours4.8 (365 ratings)View course

What you'll learn

The basic principles of descriptive and inferential statistics
Use statistical analyses to make data-driven decisions
How to formulate and test hypotheses and take action based on the outcome

Skills you'll gain

Descriptive Statistics, Regression Analysis, Statistical Modeling, Sampling (Statistics), Spreadsheet Software, Time Series Analysis and Forecasting, Statistics, Analytics, Statistical Inference, Bayesian Statistics, Statistical Analysis, Tableau Software, Data Analysis, Statistical Hypothesis Testing, Statistical Methods, Marketing Analytics, Probability & Statistics, and Data Modeling

Introduction to Data Management

Course 515 hours4.8 (109 ratings)View course

What you'll learn

How to apply the fundamentals of data collection and data quality management
Different type data storage solutions and architectures, including big data management and how they are used
The fundamentals of data privacy and compliance, as well as the basics of machine learning

Skills you'll gain

Data Storage, Data Security, Data Analysis, Machine Learning, Data Governance, Data-Driven Decision-Making, Data Quality, Data Collection, Data Architecture, Information Privacy, Big Data, Data Visualization Software, and Data Management

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Brandon Larkin

Meta

2 Courses33,677 learners

Brandi Robinson

2 Courses40,750 learners

Anke Audenaert

Meta

41 Courses963,588 learners

Victor Geislinger

Meta

1 Course26,396 learners

Offered by

Meta

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Frequently asked questions

Learners who want to learn fundamental data analysis skills to jump-start a career as an entry-level data analyst.

Aptly provides online education where technology disrupts. Aptly’s team of educators, digital marketers, marketing analysts, and instructional designers combine their experience from academia and the tech industry into hands-on, applied education programs. Together with Meta, they have helped hundreds of thousands of students, employees, job seekers, marketers, and businesses gain the skills and knowledge to succeed in the digital economy.

Approximately 5 months, 5-7 hours per week

Should you decide to take all or multiple courses, we highly encourage you to take them in the suggested order, as we have designed the courses to work in sequence.

Course 1 - Introduction to Data Analytics
Course 2 - Data Analysis with Spreadsheets and SQL
Course 3 - Python Data Analytics
Course 4 - Statistics Foundations
Course 5 - Introduction to Data Management

Meta Data Analyst with GenAI Professional Certificate

What you'll learn

Overview

Skills you'll gain

Tools you'll learn

What’s included