Course
Introduction to Azure
- BasicSkill Level
- 4.8+
- 740 reviews
Explore Azure services like Compute, Storage, and Automation, with hands-on experience.
Cloud
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
or
Course
Explore Azure services like Compute, Storage, and Automation, with hands-on experience.
Cloud
Course
Learn to perform linear and logistic regression with multiple explanatory variables.
Probability & Statistics
Course
Learn how to structure your PostgreSQL queries to run in a fraction of the time.
Software Development
Course
Analyze data smarter with Gemini in Google Sheets. Use AI-powered insights, formula suggestions, and automation to simplify spreadsheets and boost productivity.
Artificial Intelligence
Course
You will investigate a dataset from a fictitious company called Databel in Tableau, and need to figure out why customers are churning.
Data Visualization
Course
In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.
Data Engineering
Course
Master data manipulation and analysis techniques such as CASE statements, subqueries, and CTEs in Snowflake.
Data Manipulation
Course
Master data fluency! Learn skills for individuals and organizations, understand behaviors, and build a data-fluent culture.
Data Literacy
Course
Learn to bring data into Microsoft Fabric, covering Pipelines, Dataflows, Shortcuts, Semantic Models, security, and model refresh.
Other
Course
Build SQL skills by writing AI prompts that generate queries for sorting, grouping, filtering, and categorizing data.
Data Manipulation
Course
This course equips security and data protection leaders with strategies to securely manage AI within their organizations.
Cloud
Course
Map agent types to your KPIs and explore use cases that solve problems, learn how Gemini Enterprise empowers you to build and orchestrate the right agents.
Cloud
Course
You unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI.
Cloud
Course
Master strategic data management for business excellence.
Data Management
Course
Practice data storytelling using real-world examples! Communicate complex insights effectively with a dataset of certified green businesses.
Data Literacy
Course
Master SQL Server programming by learning to create, update, and execute functions and stored procedures.
Software Development
Course
Learn key techniques to optimize Java performance, from algorithm efficiency to JVM tuning and multithreading.
Software Development
Course
Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.
Probability & Statistics
Course
In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.
Machine Learning
Course
Unlock Alteryx for data transformation, mastering Crosstab, Transpose, and workflow optimization in this interactive course.
Data Manipulation
Course
Learn how to transform raw data into clean, reliable models with dbt through hands-on, real-world exercises.
Data Engineering
Course
In this course, students will learn to write queries that are both efficient and easy to read and understand.
Software Development
Course
Load, automate, and optimize data pipelines in Snowflake using COPY INTO, Snowpipe, streams, tasks, dynamic tables, and query performance tools.
Data Engineering
Course
Explore ways to work with date and time data in SQL Server for time series analysis
Data Manipulation
Course
Dive into the world of digital transformation and equip yourself to be an agent of change in a rapidly evolving digital landscape.
Data Literacy
Course
Learn to secure, govern, and manage Snowflake at scale. Cover RBAC, data masking, cost monitoring, Time Travel, and secure data sharing.
Data Management
Course
Learn essential finance math skills with practical Excel exercises and real-world examples.
Applied Finance
Course
In this course, youll learn the basics of relational databases and how to interact with them.
Data Manipulation
Course
You will use Net Revenue Management techniques in Excel for a Fast Moving Consumer Goods company.
Applied Finance
Course
Learn how to clean data with Apache Spark in Python.
Data Preparation
Data science is an area of expertise focused on gaining information from data. Using programming skills, scientific methods, algorithms, and more, data scientists analyze data to form actionable insights.
You’ll need to learn a programming language such as Python or R and master the principles of math and statistics. Knowledge of data analysis methods and data science tools is also essential. There are many ways to learn data science. As well as formal means of education, such as a degree or university study, there are plenty of other resources to help you learn at your own pace. As well as online courses and tutorials, there are books, videos, and more.
As well as knowledge of mathematics and statistics, data scientists need programming skills in languages such as Python, R, and SQL. Additionally, data science requires the ability to work with large data sets, knowledge of data visualization, data wrangling, and database management. Skills in machine learning and deep learning can also be useful.
In a professional capacity, almost every industry can use data science to some degree. Healthcare organizations use data science to detect and cure diseases, while finance companies use it to detect and prevent fraud. All kinds of industries use data science for marketing, such as building recommendation systems and analyzing customer churn.
Yes, data science is among the fastest-growing sectors in the US and worldwide. It’s also one of the best-paid careers out there. According to data from Payscale, experience data scientists earn an average of $97,609 and have a satisfaction rating of four stars out of five in the US.
There are a few things to consider here. First, data science degrees can be competitive to get onto, often requiring consistently high grades. Similarly, many of the skills required for data science require a lot of study and patience. It can take several months to master all of the necessary basics, as well as a lot of practical experience to secure an entry-level position.
Yes, you’ll need some coding experience in languages such as Python, R, SQL, Java, and C/C++. However, due to its relatively simple syntax, Python programming language is often the preferred choice among newcomers.
For a person with no prior coding experience and/or mathematical background, it can typically take 7 to 12 months of intensive studies to be at the level of an entry-level data scientist. However, it is important to remember that learning only the theoretical basis of data science may not make you a real data scientist.
Once you’ve mastered the foundations of data science, you can then specialize in a variety of areas, including machine learning, artificial intelligence, big data analysis, business analytics and intelligence, data mining, and more.
Make progress on the go with our mobile courses and daily 5-minute coding challenges.