How To Become An Instructor ?
Become an Instructor and teach data courses online using your preferred tool and preferred language. Enjoy the flexibility to create engaging courses, share expertise globally, and earn passive income. Benefit from a growing demand for data skills, build a personal brand, and empower learners to excel in data-driven roles. Join a DigDatum community of educators, access resources for course creation, and inspire students with interactive online lessons. With online teaching, reach a diverse audience, contribute to skill development, and make a meaningful impact in the data analysis field. Turn your passion for data into a rewarding teaching journey today!
When you sign up to become an instructor on
the DigDatum platform, you agree to abide by these Instructor Terms (“Terms“). These Terms cover details about the aspects of the DigDatum platform relevant to instructors and are incorporated by reference into our Terms of Use, the general terms that govern your use of our Services. Any capitalized terms that aren’t defined in these Terms are defined as specified in the Terms of Use.
As an instructor, you are contracting directly with DigDatum, regardless of whether another DigDatum subsidiary facilitates payments to you. Read more
Here is a list of sample courses using various data tools. You can create your own course.
- Introduction to Data Analysis with Excel
- Advanced Data Analysis with Excel
- Data Visualization with Power BI
- Data Modeling and Power Pivot Mastery
- SQL Fundamentals for Data Analysis
- Python for Data Analysis and Visualization
- R Programming for Statistical Analysis
- Tableau Essentials for Data Visualization
- Google Sheets for Data Analysis
- Introduction to Business Intelligence Tools
- Data Cleaning and Transformation with OpenRefine
- Introduction to Data Mining with Weka
- Predictive Analytics using SAS
- Machine Learning Fundamentals with TensorFlow
- Big Data Analytics with Hadoop
- Data Engineering with Apache Spark
- Web Scraping for Data Collection
- Geospatial Data Analysis with GIS Tools
- Text Mining and Sentiment Analysis
Data Ethics and Privacy in Analytics