Course
Data Modeling in Sigma
- BasicSkill Level
- 4.7+
- 336
Stop rewriting the same joins and calculations, and dive into well-governed, scalable analytics using Sigma data models.
Reporting
Data, AI, and Cloud Courses
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By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.675 Courses
Course
Building Chatbots in Python
- IntermediateSkill Level
- 4.6+
- 336
Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.
Machine Learning
Course
AI-Assisted Product Launch
- BasicSkill Level
- 4.4+
- 333
Analyze market dynamics and craft a strategic entry plan for an EV manufacturer using generative AI.
Artificial Intelligence
Course
Calculations in Sigma
- BasicSkill Level
- 4.8+
- 332
Build dynamic Sigma calculations to explore data, automate logic, and uncover trends with practical business examples.
Data Manipulation
Course
Case Study: Ecommerce Analysis in Power BI
- IntermediateSkill Level
- 4.7+
- 332
In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.
Data Visualization
Course
AI-Assisted Restaurant Planning
- BasicSkill Level
- 4.6+
- 332
Interact with a customized GPT and use your prompting skills to plan and open your restaurant.
Artificial Intelligence
Course
Digital Transformation with Google Cloud
- BasicSkill Level
- 4.8+
- 330
This course provides an overview of the opportunities and challenges companies encounter in their digital transformation journey.
Cloud
Course
Azure Compute Solutions
- IntermediateSkill Level
- 4.6+
- 329
Learn how containers work in Azure, including registries, ACI, AKS basics, scaling, monitoring, and troubleshooting.
Cloud
Course
Designing Machine Learning Workflows in Python
- AdvancedSkill Level
- 4.4+
- 328
Learn to build pipelines that stand the test of time.
Machine Learning
Course
Case Study: Analyzing City Time Series Data in R
- IntermediateSkill Level
- 4.7+
- 327
Strengthen your knowledge of the topics covered in Manipulating Time Series in R using real case study data.
Probability & Statistics
Course
Querying a PostgreSQL Database in Java
- AdvancedSkill Level
- 4.6+
- 327
Connect Java to PostgreSQL with JDBC. Write secure queries, manage transactions, and handle large datasets efficiently.
Software Development
Course
Transactions and Error Handling in PostgreSQL
- IntermediateSkill Level
- 4.6+
- 325
Ensure data consistency by learning how to use transactions and handle errors in concurrent environments.
Software Development
Course
GARCH Models in Python
- IntermediateSkill Level
- 4.7+
- 324
Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.
Applied Finance
Course
Introduction to Data Versioning with DVC
- IntermediateSkill Level
- 4.5+
- 323
Explore Data Version Control for ML data management. Master setup, automate pipelines, and evaluate models seamlessly.
Machine Learning
Course
Customer Segmentation in Python
- IntermediateSkill Level
- 4.5+
- 323
Learn how to segment customers in Python.
Data Manipulation
Course
Fundamentals of Bayesian Data Analysis in R
- IntermediateSkill Level
- 4.8+
- 318
Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.
Probability & Statistics
Course
Advanced Deep Learning with Keras
- IntermediateSkill Level
- 4.7+
- 318
Learn how to develop deep learning models with Keras.
Artificial Intelligence
Course
Gemini in Google Sheets
- BasicSkill Level
- 4.6+
- 318
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
Gemini in Google Docs
- BasicSkill Level
- 4.7+
- 317
Write and edit faster with Gemini in Google Docs. Get AI-powered drafting, rewriting, and content suggestions to create clear, polished documents effortlessly.
Artificial Intelligence
Course
Inference for Numerical Data in R
- AdvancedSkill Level
- 4.4+
- 312
In this course youll learn techniques for performing statistical inference on numerical data.
Probability & Statistics
Course
Case Study: Exploratory Data Analysis in R
- BasicSkill Level
- 4.3+
- 312
Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.
Exploratory Data Analysis
Course
Recurrent Neural Networks (RNNs) for Language Modeling with Keras
- AdvancedSkill Level
- 4.8+
- 311
Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.
Artificial Intelligence
Course
Hierarchical and Recursive Queries in SQL Server
- AdvancedSkill Level
- 4.7+
- 311
Learn how to write recursive queries and query hierarchical data structures.
Software Development
Course
Building Agentic Workflows with LlamaIndex
- AdvancedSkill Level
- 4.4+
- 309
Build AI agentic workflows that can plan, search, remember, and collaborate, using LlamaIndex.
Artificial Intelligence
Course
Optimizing Code in Java
- AdvancedSkill Level
- 4.7+
- 307
Learn key techniques to optimize Java performance, from algorithm efficiency to JVM tuning and multithreading.
Software Development
Course
Introduction to Portfolio Analysis in R
- BasicSkill Level
- 4.5+
- 306
Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.
Applied Finance
Course
Practicing Machine Learning Interview Questions in Python
- AdvancedSkill Level
- 4.5+
- 303
Sharpen your knowledge and prepare for your next interview by practicing Python machine learning interview questions.
Machine Learning
Course
Gen AI Agents: Transform Your Organization
- BasicSkill Level
- 4.7+
- 302
This course explores how organizations can use custom gen AI agents to help tackle specific business challenges.
Cloud
Course
Cleaning Data in SQL Server Databases
- IntermediateSkill Level
- 4.6+
- 300
Develop the skills you need to clean raw data and transform it into accurate insights.
Data Preparation
Course
Case Study: Data Analysis in Databricks
- AdvancedSkill Level
- 4.1+
- 300
Learn to analyze Airbnb data using SQL in Databricks, create dashboards, and derive actionable insights.
Importing & Cleaning Data
FAQs
What is data science?
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.
How can I learn data science?
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.
What skills are required for data science?
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.
What can I use data science for?
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.
Is data science a good career?
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.
Is it difficult to become a data scientist?
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.
Does data science require coding?
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.
How long does it take to become a data scientist?
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.
What topics can I study within data science?
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.