Course
Advanced AI-Assisted Coding for Developers
- AdvancedSkill Level
- 4.9+
- 40 reviews
Learn to use AI as a senior engineering partner for code analysis, performance optimization, security, and software architecture decisions.
Artificial Intelligence
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
or
Course
Learn to use AI as a senior engineering partner for code analysis, performance optimization, security, and software architecture decisions.
Artificial Intelligence
Course
Stop rewriting the same joins and calculations, and dive into well-governed, scalable analytics using Sigma data models.
Reporting
Course
Learn about ARIMA models in Python and become an expert in time series analysis.
Machine Learning
Course
Gain an overview of AI Agents. Discover how AI Agents use autonomous action and reasoning to solve complex problems.
Cloud
Course
Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.
Data Manipulation
Course
In this course youll learn to use and present logistic regression models for making predictions.
Machine Learning
Course
Learn how to make GenAI models truly reflect human values while gaining hands-on experience with advanced LLMs.
Artificial Intelligence
Course
Learn how to make attractive visualizations of geospatial data in Python using the geopandas package and folium maps.
Data Visualization
Course
Build interactive AI apps in Sigma using user input, actions, and polished interfaces, no coding required.
Reporting
Course
Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.
Probability & Statistics
Course
Build dynamic Sigma calculations to explore data, automate logic, and uncover trends with practical business examples.
Data Manipulation
Course
Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.
Artificial Intelligence
Course
Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.
Probability & Statistics
Course
Learn to design and run your own Monte Carlo simulations using Python!
Probability & Statistics
Course
Learn how to use and create sub-agents in Claude Code to manage context, delegate tasks, and build workflows that keep your conversation clean and focused.
Artificial Intelligence
Course
Discover how to use the income statement and balance sheet in Power BI
Applied Finance
Course
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
Learn key techniques to optimize Java performance, from algorithm efficiency to JVM tuning and multithreading.
Software Development
Course
Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!
Probability & Statistics
Course
Discover Snowflake window functions to solve complex data problems with rankings, partitions, and rolling calculations.
Data Manipulation
Course
Exploring Data Transformation with Google Cloud
Cloud
Course
Learn how to efficiently collect and download data from any website using R.
Data Preparation
Course
This course introduces Google’s gen AI applications, such as Google Workspace with Gemini and NotebookLM.
Cloud
Course
Explore Alteryx Designer in a retail data case study to boost sales analysis and strategic decision-making.
Data Preparation
Course
This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.
Probability & Statistics
Course
In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.
Data Visualization
Course
In this Power BI case study you’ll play the role of a junior trader, analyzing mortgage trading and enhancing your data modeling and financial analysis skills.
Applied Finance
Course
You unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI.
Cloud
Course
Master data fluency! Learn skills for individuals and organizations, understand behaviors, and build a data-fluent culture.
Data Literacy
Course
Explore ways to work with date and time data in SQL Server for time series analysis
Data Manipulation
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.