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Introduction to Bash Scripting
- IntermediateSkill Level
- 4.7+
- 1.1K
Bash scripting allows you to build analytics pipelines in the cloud and work with data stored across multiple files.
Software Development
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Introduction to Deep Learning with Keras
- IntermediateSkill Level
- 4.6+
- 1.1K
Learn to start developing deep learning models with Keras.
Artificial Intelligence
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Feature Engineering for Machine Learning in Python
- IntermediateSkill Level
- 4.6+
- 1.1K
Create new features to improve the performance of your Machine Learning models.
Machine Learning
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Introduction to Writing Functions in R
- BasicSkill Level
- 4.3+
- 1.1K
Take your R skills up a notch by learning to write efficient, reusable functions.
Software Development
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Introduction to Generative AI in Snowflake
- IntermediateSkill Level
- 4.6+
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Learn to build AI applications using Snowflake Cortexs built-in LLM functions for text analysis, generation, and multi-step workflows.
Artificial Intelligence
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Intermediate SQL Server
- IntermediateSkill Level
- 4.7+
- 1.1K
In this course, you will use T-SQL, the flavor of SQL used in Microsofts SQL Server for data analysis.
Software Development
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Analyzing Marketing Campaigns with pandas
- BasicSkill Level
- 4.5+
- 1K
Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!
Exploratory Data Analysis
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Introduction to R for Finance
- BasicSkill Level
- 4.6+
- 1K
Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.
Applied Finance
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Deep Learning for Text with PyTorch
- AdvancedSkill Level
- 4.4+
- 1K
Discover the exciting world of Deep Learning for Text with PyTorch and unlock new possibilities in natural language processing and text generation.
Artificial Intelligence
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Sampling in R
- IntermediateSkill Level
- 4.4+
- 1K
Master sampling to get more accurate statistics with less data.
Probability & Statistics
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Introduction to NoSQL
- BasicSkill Level
- 4.7+
- 1K
Conquer NoSQL and supercharge data workflows. Learn Snowflake to work with big data, Postgres JSON for handling document data, and Redis for key-value data.
Data Engineering
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Microsoft Copilot in Excel
- BasicSkill Level
- 4.4+
- 993
Stop fighting Excel and start talking to it! Use Copilot in Excel to clean data, build charts, and get answers faster.
Artificial Intelligence
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Connecting Data in Tableau
- BasicSkill Level
- 4.7+
- 990
Learn to connect Tableau to different data sources and prepare the data for a smooth analysis.
Data Preparation
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Vibe Coding with Replit
- BasicSkill Level
- 4.6+
- 985
Learn vibe coding with Replit. Build apps like a Typeform clone, and master securing and deploying Replit apps.
Artificial Intelligence
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Introduction to Statistics in Google Sheets
- BasicSkill Level
- 4.4+
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Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.
Probability & Statistics
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Model Validation in Python
- IntermediateSkill Level
- 4.6+
- 955
Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.
Machine Learning
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Reporting in SQL
- IntermediateSkill Level
- 4.6+
- 947
Learn how to build your own SQL reports and dashboards, plus hone your data exploration, cleaning, and validation skills.
Reporting
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Time Series Analysis in R
- IntermediateSkill Level
- 4.7+
- 941
Learn the core techniques necessary to extract meaningful insights from time series data.
Probability & Statistics
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Artificial Intelligence Governance
- BasicSkill Level
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- 934
Learn AI governance with Collibra. Build, embed, and scale responsible AI using tools, frameworks, and MLOps workflows.
Artificial Intelligence
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Data Storytelling Case Study: Green Businesses
- BasicSkill Level
- 4.5+
- 923
Practice data storytelling using real-world examples! Communicate complex insights effectively with a dataset of certified green businesses.
Data Literacy
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Explainable Artificial Intelligence (XAI) Concepts
- BasicSkill Level
- 4.5+
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Understand the role and real-world realities of Explainable Artificial Intelligence (XAI) with this beginner friendly course.
Artificial Intelligence
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Understanding Microsoft Azure Management and Governance
- BasicSkill Level
- 4.6+
- 918
Master Azure Management and Governance with our comprehensive course, ideal for data professionals seeking cloud expertise.
Cloud
Course
Case Study: Analyzing Customer Churn in Tableau
- BasicSkill Level
- 4.5+
- 897
You will investigate a dataset from a fictitious company called Databel in Tableau, and need to figure out why customers are churning.
Data Visualization
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Understanding the EU AI Act
- BasicSkill Level
- 4.5+
- 895
Get your AI Act together! Understand the obligations, risks, and requirements of the EU AI Act.
Artificial Intelligence
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Machine Learning with PySpark
- AdvancedSkill Level
- 4.7+
- 892
Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.
Machine Learning
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Data Management in Databricks
- BasicSkill Level
- 4.5+
- 881
Learn data management in Databricks with Delta Lake, including ACID transactions, schema enforcement, and security.
Data Management
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Machine Learning for Time Series Data in Python
- AdvancedSkill Level
- 4.6+
- 876
This course focuses on feature engineering and machine learning for time series data.
Machine Learning
Course
Developing Python Packages
- IntermediateSkill Level
- 4.4+
- 870
Learn to create your own Python packages to make your code easier to use and share with others.
Software Development
Course
Marketing Analytics for Business
- BasicSkill Level
- 4.7+
- 868
Discover how Marketing Analysts use data to understand customers and drive business growth.
Leadership
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A/B Testing in Python
- IntermediateSkill Level
- 4.4+
- 859
Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.
Probability & Statistics
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.