EdX

Data Analytics Basics for Everyone (edX)

Offered by IBM,
Data Analytics Basics for Everyone (edX)

Learn the fundamentals of Data Analytics and gain an understanding of the data ecosystem, the process and lifecycle of data analytics, career opportunities, and the different learning paths you can take to be a Data Analyst. In this course, you will learn about the various components of a modern data ecosystem and the role Data Analysts, Data Scientists, and Data Engineers play in this ecosystem.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

You will gain an understanding of data structures, file formats, sources of data, and data repositories. You will understand what Big Data is and the features and uses of some of the Big Data processing tools.
This course will introduce you to the key tasks a Data Analyst performs in a typical day. This includes how they identify, gather, wrangle, mine and analyze data, and finally communicate their findings to different stakeholders impactfully. You will be introduced to some of the tools Data Analysts use for each of these tasks.
You will learn about the features and use of relational and non-relational databases, data warehouses, data marts, and data lakes. You will understand how ETL, or Extract-Transform-Load, process converts raw data into analysis-ready data. And what are some of the specific languages used by data analytics to extract, prepare, and analyze data.
By the end of this course you will know about the various career opportunities available in the field of Data Analytics, and the different learning paths you can consider to gain entry into this field.
The course ends with some exercises and a hands-on lab to test your understanding of some of the basic data gathering, wrangling, mining, analysis, and visualization tasks.
This course is part of the Data Analyst Professional Certificate.

What you'll 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
  • Explain the use for different types of data repositories, the ETL process, and Big Data platforms
  • Describe the process and tools for gathering data, wrangling data, mining and analyzing data, and visualizing data
  • List the different career opportunities in Data Analysis and resources for getting skilled in this domain
  • Demonstrate your understanding of gathering, wrangling, mining, analyzing, and visualizing data
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Introduction to Computer Science and Programming (edX) EdX
Tokyo Institute of Technology,TokyoTechX

Introduction to Computer Science and Programming (edX)

CS: Programming

The term “Computation” refers to the action performed by a computer. A computation can be a basic operation and it can also be a sophisticated computer simultation requiring a large amount of data and substantial resources. This course aims at introducing learners with no prior knowledge to basics and key concepts of computer science. By following the lectures and exercises of this course you will have an understanding of algorithms and you will get a real experience of programming using the language Ruby.

Self Paced
Self-Paced
Programming Artificial Intelligence Big Data
Details
Big Data Capstone Project (edX) EdX
University of Adelaide,AdelaideX

Big Data Capstone Project (edX)

Statistics & Data Analysis Data Science

Further develop your knowledge of big data by applying the skills you have learned to a real-world data science project. This project will give you the opportunity to deepen your learning by giving you valuable experience in evaluating, selecting and applying relevant data science techniques, principles and theory to a data science problem. This project will see you plan and execute a reasonably substantial project and demonstrate autonomy, initiative and accountability.

Self Paced
Self-Paced
Big Data Data Science Data Analytics
Details
Visualizing Data with Python (edX) EdX
IBM

Visualizing Data with Python (edX)

Statistics & Data Analysis CS: Programming

Data visualization is the graphical representation of data in order to interactively and efficiently convey insights to clients, customers, and stakeholders in general. "A picture is worth a thousand words." We are all familiar with this expression. It especially applies when trying to explain the insights obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data. One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way.

Self Paced
Self-Paced
Python Maps Charts
Details
Data Science: R Basics (edX) EdX
HarvardX,Harvard University

Data Science: R Basics (edX)

Statistics & Data Analysis Data Science

Build a foundation in R and learn how to wrangle, analyze, and visualize data. This course will introduce you to the basics of R programming. You can better retain R when you learn it to solve a specific problem, so you’ll use a real-world dataset about crime in the United States. You will learn the R skills needed to answer essential questions about differences in crime across the different states.

Self Paced
Self-Paced
Probability Machine Learning Inference
Details
Data Science and Machine Learning Capstone Project (edX) EdX
IBM

Data Science and Machine Learning Capstone Project (edX)

Statistics & Data Analysis Data Science

Create a project that you can use to showcase your Data Science skills to prospective employers. Apply various data science and machine learning techniques to analyze and visualize a data set involving a real life business scenario and build a predictive model. Now that you've taken several courses on data science and machine learning, it’s time to put your learning to work on a data problem involving a real life scenario. Employers really care about how well you can apply your knowledge and skills to solve real world problems, and the work you do in this capstone project will make you stand out in the job market.

Self Paced
Self-Paced
Python Machine Learning Data Science
Details
Data Science: Probability (edX) EdX
HarvardX,Harvard University

Data Science: Probability (edX)

Statistics & Data Analysis Data Science

Learn probability theory — essential for a data scientist — using a case study on the financial crisis of 2007–2008. In this course, you will learn valuable concepts in probability theory. The motivation for this course is the circumstances surrounding the financial crisis of 2007–2008. Part of what caused this financial crisis was that the risk of some securities sold by financial institutions was underestimated. To begin to understand this very complicated event, we need to understand the basics of probability.

Self Paced
Self-Paced
Probability Monte Carlo Method Data Science
Details
Unix Tools: Data, Software and Production Engineering (edX) EdX
Delft University of Technology,DelftX

Unix Tools: Data, Software and Production Engineering (edX)

Computer Science

Grow from being a Unix novice to Unix wizard status! Process big data, analyze software code, run DevOps tasks and excel in your everyday job through the amazing power of the Unix shell and command-line tools. Processing information is the hallmark of all modern organizations, which are increasingly digital: absorbing, processing and generating information is a key element of their business.

Self Paced
Self-Paced
Data Software Engineering Unix
Details