Data Management
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
Marketing Analytics in Google Sheets
- IntermediateSkill Level
- 4.5+
- 382
Learn how to ensure clean data entry and build dynamic dashboards to display your marketing data.
Reporting
Course
Introduction to AI Apps in Sigma
- BasicSkill Level
- 4.8+
- 379
Build interactive AI apps in Sigma using user input, actions, and polished interfaces, no coding required.
Reporting
Course
Winning a Kaggle Competition in Python
- AdvancedSkill Level
- 4.8+
- 379
Learn how to approach and win competitions on Kaggle.
Machine Learning
Course
Time Series Analysis in Power BI
- IntermediateSkill Level
- 4.5+
- 379
Learn to analyze data over time with this practical course on Time Series Analysis in Power BI. Work with real datasets & practice common techniques.
Data Visualization
Course
Introduction to Network Analysis in Python
- IntermediateSkill Level
- 4.7+
- 376
This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.
Probability & Statistics
Course
Fine-Tuning with Llama 3
- IntermediateSkill Level
- 4.6+
- 375
Fine-tune Llama for custom tasks using TorchTune, and learn techniques for efficient fine-tuning such as quantization.
Artificial Intelligence
Course
Experimental Design in R
- IntermediateSkill Level
- 4.3+
- 372
In this course youll learn about basic experimental design, a crucial part of any data analysis.
Probability & Statistics
Course
Transactions and Error Handling in SQL Server
- IntermediateSkill Level
- 4.7+
- 371
Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.
Software Development
Course
AI for Sales
- BasicSkill Level
- 4.5+
- 368
Tackle your sales work in an AI-first way! Learn to automate prospecting, draft personalized emails, and streamline CRM tasks using AI.
Artificial Intelligence
Course
Introduction to Python in Power BI
- IntermediateSkill Level
- 4.5+
- 368
Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.
Data Manipulation
Course
Building AI Agents with CrewAI
- IntermediateSkill Level
- 4.5+
- 367
Build AI teams that work together, automate workflows, and generate content with CrewAI.
Artificial Intelligence
Course
Categorical Data in the Tidyverse
- BasicSkill Level
- 4.4+
- 367
Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.
Data Manipulation
Course
Decoding Decision Modeling
- BasicSkill Level
- 4.7+
- 362
Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.
Data Literacy
Course
Case Study: Analyzing Sales Data in Alteryx
- BasicSkill Level
- 4.8+
- 361
Explore Alteryx Designer in a retail data case study to boost sales analysis and strategic decision-making.
Data Preparation
Course
Improving Your Data Visualizations in Python
- IntermediateSkill Level
- 4.4+
- 361
Learn to construct compelling and attractive visualizations that help communicate results efficiently and effectively.
Data Visualization
Course
HR Analytics: Exploring Employee Data in R
- IntermediateSkill Level
- 4.4+
- 359
Learn how to manipulate, visualize, and perform statistical tests through a series of HR analytics case studies.
Exploratory Data Analysis
Course
Analyzing Financial Statements in Python
- IntermediateSkill Level
- 4.2+
- 357
Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.
Applied Finance
Course
Case Study: Inventory Analysis in Power BI
- IntermediateSkill Level
- 4.8+
- 355
This Power BI case study follows a real-world business use case on tackling inventory analysis using DAX and visualizations.
Data Visualization
Course
Monitoring Machine Learning in Python
- AdvancedSkill Level
- 4.6+
- 354
This course covers everything you need to know to build a basic machine learning monitoring system in Python
Machine Learning
Course
Foundations of Probability in Python
- IntermediateSkill Level
- 4.5+
- 353
Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.
Probability & Statistics
Course
Intermediate R for Finance
- BasicSkill Level
- 4.3+
- 353
Learn about how dates work in R, and explore the world of if statements, loops, and functions using financial examples.
Applied Finance
Course
Baseball Data Visualization in Power BI
- BasicSkill Level
- 4.7+
- 349
Discover how to analyze and visualize baseball data using Power BI. Create scatter plots, tornado charts, and gauges to bring baseball insights alive.
Data Visualization
Course
Building and Optimizing Triggers in SQL Server
- IntermediateSkill Level
- 4.7+
- 349
Learn how to design and implement triggers in SQL Server using real-world examples.
Software Development
Course
Data Fluency
- BasicSkill Level
- 4.5+
- 348
Master data fluency! Learn skills for individuals and organizations, understand behaviors, and build a data-fluent culture.
Data Literacy
Course
Supply Chain Analytics in Python
- IntermediateSkill Level
- 4.7+
- 345
Leverage the power of Python and PuLP to optimize supply chains.
Exploratory Data Analysis
Course
Interactive Maps with leaflet in R
- BasicSkill Level
- 4.6+
- 343
Learn how to produce interactive web maps with ease using leaflet.
Data Visualization
Course
Multi-Modal Models with Hugging Face
- IntermediateSkill Level
- 4.5+
- 342
Combine text, images, audio, and video with the latest AI models from Hugging Face, and generate new images and videos!
Artificial Intelligence
Course
Object-Oriented Programming with S3 and R6 in R
- AdvancedSkill Level
- 4.5+
- 341
Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.
Software Development
Course
Gen AI: Beyond the Chatbot
- BasicSkill Level
- 4.7+
- 337
This course aims to move beyond the basic understanding of chatbots to explore the true potential of generative AI for your organization.
Cloud
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.