Course
Manipulating Time Series Data in Python
- IntermediateSkill Level
- 4.8+
- 1.7K
In this course youll learn the basics of working with time series data.
Data Manipulation
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Course
Image Processing in Python
- IntermediateSkill Level
- 4.8+
- 1.7K
Learn to process, transform, and manipulate images at your will.
Machine Learning
Course
Introduction to Data Engineering
- IntermediateSkill Level
- 4.8+
- 1.7K
Learn about the world of data engineering in this short course, covering tools and topics like ETL and cloud computing.
Data Engineering
Course
Vector Databases for Embeddings with Pinecone
- IntermediateSkill Level
- 4.8+
- 1.6K
Discover how the Pinecone vector database is revolutionizing AI application development!
Artificial Intelligence
Course
Introduction to Data Modeling in Snowflake
- IntermediateSkill Level
- 4.8+
- 1.6K
Step right into the dynamic world of data modeling with Snowflake!
Data Engineering
Course
Introduction to Deep Learning in Python
- IntermediateSkill Level
- 4.8+
- 1.6K
Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.
Artificial Intelligence
Course
Intermediate Regression in R
- IntermediateSkill Level
- 4.8+
- 1.6K
Learn to perform linear and logistic regression with multiple explanatory variables.
Probability & Statistics
Course
Introduction to Model Context Protocol (MCP)
- IntermediateSkill Level
- 4.9+
- 1.6K
Integrate AI/LLM applications with APIs, databases, and filesystems easier than ever before with the Model Context Protocol (MCP).
Artificial Intelligence
Course
Financial Analysis in Power BI
- IntermediateSkill Level
- 4.9+
- 1.6K
Learn how to perform financial analysis in Power BI or apply any existing financial skills using Power BI data visualizations.
Applied Finance
Course
Introduction to Object-Oriented Programming in Java
- IntermediateSkill Level
- 4.8+
- 1.5K
Learn key object-oriented programming concepts, from basic classes and objects to advanced topics like inheritance and polymorphism.
Software Development
Course
Intermediate Power Query in Excel
- IntermediateSkill Level
- 4.8+
- 1.5K
Building on your foundational Power Query in Excel knowledge, this intermediate course takes you to the next level of data transformation mastery
Data Preparation
Course
Linear Classifiers in Python
- IntermediateSkill Level
- 4.8+
- 1.5K
In this course you will learn the details of linear classifiers like logistic regression and SVM.
Machine Learning
Course
Analyzing Business Data in SQL
- IntermediateSkill Level
- 4.9+
- 1.5K
Learn to write SQL queries to calculate key metrics that businesses use to measure performance.
Reporting
Course
Intermediate Python for Finance
- IntermediateSkill Level
- 4.8+
- 1.5K
Build on top of your Python skills for Finance, by learning how to use datetime, if-statements, DataFrames, and more.
Applied Finance
Course
Working with Categorical Data in Python
- IntermediateSkill Level
- 4.8+
- 1.5K
Learn how to manipulate and visualize categorical data using pandas and seaborn.
Data Manipulation
Course
Working with Llama 3
- IntermediateSkill Level
- 4.8+
- 1.4K
Explore the latest techniques for running the Llama LLM locally and integrating it within your stack.
Artificial Intelligence
Course
Streamlined Data Ingestion with pandas
- IntermediateSkill Level
- 4.8+
- 1.4K
Learn to acquire data from common file formats and systems such as CSV files, spreadsheets, JSON, SQL databases, and APIs.
Data Preparation
Course
Building AI Agents with Google ADK
- IntermediateSkill Level
- 4.8+
- 1.3K
Build a customer-support assistant step-by-step with Google’s Agent Development Kit (ADK).
Artificial Intelligence
Course
Reshaping Data with pandas
- IntermediateSkill Level
- 4.8+
- 1.3K
Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.
Data Manipulation
Course
Applying SQL to Real-World Problems
- IntermediateSkill Level
- 4.9+
- 1.3K
Find tables, store and manage new tables and views, and write maintainable SQL code to answer business questions.
Reporting
Course
Software Development with Cursor
- IntermediateSkill Level
- 4.8+
- 1.3K
Build production-ready code with Cursor. Learn AI prompts, refactoring, testing, and advanced workflows.
Artificial Intelligence
Course
Supervised Learning in R: Classification
- IntermediateSkill Level
- 4.7+
- 1.3K
In this course you will learn the basics of machine learning for classification.
Machine Learning
Course
Intermediate Docker
- IntermediateSkill Level
- 4.8+
- 1.2K
Master multi-stage builds, Docker networking tools, and Docker Compose for optimal containerized applications!
Software Development
Course
Introduction to Natural Language Processing in Python
- IntermediateSkill Level
- 4.7+
- 1.2K
Learn fundamental natural language processing techniques using Python and how to apply them to extract insights from real-world text data.
Machine Learning
Course
Time Series Analysis in Python
- IntermediateSkill Level
- 4.9+
- 1.2K
In this four-hour course, you’ll learn the basics of analyzing time series data in Python.
Probability & Statistics
Course
Extreme Gradient Boosting with XGBoost
- IntermediateSkill Level
- 4.9+
- 1.2K
Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.
Machine Learning
Course
Introduction to Deep Learning with Keras
- IntermediateSkill Level
- 4.8+
- 1.2K
Learn to start developing deep learning models with Keras.
Artificial Intelligence
Course
Explainable AI in Python
- IntermediateSkill Level
- 4.8+
- 1.2K
Gain the essential skills using Scikit-learn, SHAP, and LIME to test and build transparent, trustworthy, and accountable AI systems.
Artificial Intelligence
Course
Intermediate Data Visualization with ggplot2
- IntermediateSkill Level
- 4.8+
- 1.2K
Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.
Data Visualization
Course
Responsible AI Data Management
- IntermediateSkill Level
- 4.8+
- 1.2K
Learn the theory behind responsibly managing your data for any AI project, from start to finish and beyond.
Artificial Intelligence
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.
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