Certificates in Data Analytics

Prerequisites No mathematics or computer science experience is necessary. A general understanding of computing terminology and concepts is recommended. Familarity with databases and with basic statistical concepts is helpful.
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DATA ANALYST/SCIENTIST Pick One from Each Level Level 100 Introduction to Data Analytics and Big Data Big Data Overview Introduction to Cloud Technology AWS & Cloud IT Foundations Level 200 SQL For Data Analytics Data Visualization with Tableau Data Analytics with Excel Level 300 Data Analysis with Python, SQL and Excel Introduction to Python with Data Analytics Data Visualization with Matplotlib & Seaborn Machine Learning & Data Science with Python Hadoop Programming R Programming for Data Science	DATA ANALYTICS DEVELOPER Pick One from Each Level Level 100 Introduction to Data Analytics and Big Data Big Data Overview Introduction to Cloud Technology AWS & Cloud IT Foundations Level 200 SQL For Data Analytics Data Analysis with Python, SQL and Excel Introduction to Python with Data Analytics Data Visualization with Matplotlib & Seaborn Machine Learning & Data Science with Python Hadoop Programming R Programming for Data Science Level 300 Big Data Analytics for Data Engineers Big Data On AWS Data Science with Apache Spark Advanced Topics in Artificial Intelligence	BUSINESS USER/ANALYST/MANAGER Pick One from Each Level Level 100 Introduction to Cloud Technology Big Data and Data Analytics for Managers and Business Users Level 200 AWS & Cloud IT Foundations Artificial Intelligence for Managers Data Visualization with Tableau Level 300 SQL For Data Analytics Data Analytics with Excel
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Optional Capstone Optionally, UMBC Training Centers can add a Level 300 Capstone Project to the Certificate program. In a Capstone, students would complete a Data Analytics project (working with an instructor advisor) and produce a report and presentation of their results to fellow students and optionally other work colleagues.

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