What Will You Learn?
Explain what Data Analytics is and the key steps in the Data Analytics process
Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
Describe the different types of data structures, file formats, and sources of data
Describe the data analysis process involving collecting, wrangling, mining, and visualizing data
About This Course
Provider: Coursera
Format: Online
Duration: 10 hours to complete [Approx]
Target Audience: Beginners
Learning Objectives: You'll become Proficient in End-to-End Data Analysis and Visualization after completing this free course.
Course Prerequisites: NA
Assessment and Certification: NA
Instructor: IBM
Key Topics: Data Science, Data Analysis, Data Visualization, Microsoft Excel, Spreadsheet
Topic Covered:
- - Course Introduction
- - Modern Data Ecosystem
- - Key Players in the Data Ecosystem
- - Defining Data Analysis
- - Viewpoints: What is Data Analytics?
- - Responsibilities of a Data Analyst
- - Viewpoints: Qualities and Skills to be a Data Analyst
- - Overview of the Data Analyst Ecosystem
- - Types of Data
- - Understanding Different Types of File Formats
- - Sources of Data
- - Languages for Data Professionals
- - Overview of Data Repositories
- - RDBMS
- - NoSQL
- - Data Marts, Data Lakes, ETL, and Data Pipelines
- - Foundations of Big Data
- - Big Data Processing Tools
- - Identifying Data for Analysis
- - Data Sources
- - How to Gather and Import Data
- - What is Data Wrangling?
- - Tools for Data Wrangling
- - Data Cleaning
- - Viewpoints: Data Preparation and Reliability
- - Overview of Statistical Analysis
- - What is Data Mining?
- - Tools for Data Mining
- - Overview of Communicating and Sharing Data Analysis Findings
- - Viewpoints: Storytelling in Data Analysis
- - Introduction to Data Visualization
- - Introduction to Visualization and Dashboarding Software
- - Viewpoints: Visualization Tools
- - Career Opportunities in Data Analysis
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