Skills you'll gain: Business Analysis, Data Analysis, Data Visualization, Exploratory Data Analysis, Forecasting, Probability & Statistics, Data Science, Machine Learning, Python Programming
Intermediate · Guided Project · Less Than 2 Hours
Looking to learn the best of data analytics courses? Check out Analyzing and Visualizing Data With Google Way, Python Statistics and Financial Analysis, Statistics from Stanford University, Data Analytics for Lean Six Sigma, and Python Data Processing — all free courses offered through Coursera.
For individuals who want to get started in the field of data analytics, Coursera is a great place to start. Two courses that are excellent for beginners are Introduction to Data Analytics and Foundations of Data. If you prefer to use Google's suite of data analysis tools, another great option is the Analysing and Visualising Data with Google Way course. (Analysing and Visualising Data with Google Way. Python and Amazon Web Services (AWS) are also popular tools for data analysis, so the Data Analysis with Python and Getting Started with Data Analytics on AWS courses are also great introductory courses for those interested in using these tools.
Coursera offers a great selection of advanced data analytics courses. For those looking to hone their data analysis skills, courses such as Analysis of Algorithms, Machine Learning & Data Lifecycle in Production, AutoML & Datasets & ML models and Python Statistics & Financial Analysis are ideal. Alternatively, the course Applying Data Analytics to Business in Finance is perfect for those looking to apply data analytics to business finance.
Data analytics is the science and methodology of using qualitative and quantitative approaches to extracting valuable insights into data from big data sets. This process involves finding key data points, then categorizing the data to analyze connections, patterns, relationships, and other insights. Because data is used in almost every organization, data analytics is a key part of a company’s approach to learning more about its customers, competitors, market trends, and business processes. Data analytics is usually placed into four main sections—descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics.
Data analytics is valuable to learn because it helps businesses and organizations succeed in their work. Organizations can improve their business performance and increase efficiency as they uncover and learn about various business patterns through data analytics. Getting actionable answers from raw data is a big asset to companies, and is an in-demand business skill. When you learn data analytics, you could work in B2B and B2C commerce, manufacturing, finance, healthcare, and marketing companies, as they all use data analytics to gain better knowledge about their overall business, while improving processes and growing profits.
Typical career opportunities that use data analytics are in jobs like a data analyst, quantitative analyst, data engineer, project manager, IT systems analyst, and many other similar roles involved in analyzing data. These roles are in high demand in technology companies, software agencies, large insurance companies, financial credit bureaus, consumer goods companies, financial firms, and cloud data companies. If you’re well-qualified, finding a career in data analytics isn’t difficult. But finding the right kind of company that knows what to do with data analytics effectively is important when working in this career.
When you take online courses in data analytics, you could gain a clear understanding of the fundamentals of data analytics, the big data ecosystem, and key elements of data gathering and data mining. What you learn about data analytics in online courses may help you better understand databases and data warehouses and how to explore the various cloud data mining tools. You may also learn to effectively communicate the insights gleaned from data to internal teams. This could help you become a better decision-maker.