Introduction to Data Analytics
Ready to start a career in Data Analysis but don’t know where to begin? This course presents you with a gentle introduction to Data Analysis, the role of a...
About This Course
Ready to start a career in Data Analysis but don’t know where to begin? This course presents you with a gentle introduction to Data Analysis, the role of a Data Analyst, and the tools used in this job. You will learn about the skills and responsibilities of a data analyst and hear from several data experts sharing their tips & advice to start a career. This course will help you to differentiate between the roles of Data Analysts, Data Scientists, and Data Engineers. You will familiarize yourself with the data ecosystem, alongside Databases, Data Warehouses, Data Marts, Data Lakes and Data Pipelines. Continue this exciting journey and discover Big Data platforms such as Hadoop, Hive, and Spark. By the end of this course you’ll be able to understand the fundamentals of the data analysis process including gathering, cleaning, analyzing and sharing data and communicating your insights with the use of visualizations and dashboard tools. This all comes together in the final project where it will test your knowledge of the course material, and provide a real-world scenario of data analysis tasks. This course does not require any prior data analysis, spreadsheet, or computer science experience.
Topics Covered
Frequently Asked Questions
How much does Introduction to Data Analytics cost?
Visit the Introduction to Data Analytics course page for current pricing and available discounts.
Who teaches Introduction to Data Analytics?
Introduction to Data Analytics is taught by Rav Ahuja, IBM.
What skill level is Introduction to Data Analytics for?
This course is designed for beginner learners.
Similar Courses
TensorFlow: Advanced Techniques
DeepLearning.AI
Microsoft Azure AI Fundamentals AI-900 Exam Prep
Microsoft
Data Analysts' Toolbox - Excel, Power BI, Python, & Tableau
Packt
Data Literacy: Exploring and Visualizing Data
SAS