AWS and IBM: Courses for Data Analysts from Major International Companies and Universities

This selection of online courses will help you learn the fundamentals and skills necessary for data analysts.

Python and Statistics for Financial Analysis by Hong Kong University of Science and Technology

By the end of the course, you will be able to perform the following tasks using Python:

— import, process, save, and visualize financial data in a pandas DataFrame

— manipulate existing financial data

— apply important statistical concepts in a financial context

— create a trading model using a multiple linear regression model

— evaluate the performance of the trading model using various investment indicators.

Business Analytics with Excel: Elementary to Advanced by Johns Hopkins University

This course introduces students to analytical structures used for decision-making through modeling in Excel.

These include linear and integer optimization, decision analysis, and risk modeling. First, students will familiarize themselves with the theoretical foundation, and then apply their knowledge to real-world business cases using Excel.

Getting Started with Data Analytics on AWS by Amazon Web Services

What you will learn from the course:

— explain different types of data analysis: descriptive, diagnostic, predictive, and prescriptive

— understand how to perform descriptive data analytics in the cloud with typical datasets

— how to build simple visualizations in AWS QuickSight to create descriptive analytics using S3, CloudTrail, and Athena.

The course lasts one week and consists of 10 video lessons, 9 notes, and 1 practical assignment.

IBM Data Analyst Professional Certificate by IBM

This course is designed for people who want to learn the basics of data analysis, including the use of spreadsheets and Python for sorting and structuring data.

By the end of this course, you will be able to:

— use spreadsheets and Excel to perform various data analysis tasks, such as data processing

— apply practical knowledge of Python for data analysis using Python libraries such as Pandas and NumPy

— describe the data ecosystem and write queries to access data in cloud databases using SQL and Python

— create various charts and graphs in Excel and work with IBM Cognos Analytics to build dashboards— visualize data using Python libraries such as Matplotlib.