Course
Gen AI Agents: Transform Your Organization
- BasicSkill Level
- 4.9+
- 355
This course explores how organizations can use custom gen AI agents to help tackle specific business challenges.
Cloud
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Course
Digital Transformation with Google Cloud
- BasicSkill Level
- 4.9+
- 354
This course provides an overview of the opportunities and challenges companies encounter in their digital transformation journey.
Cloud
Course
Decoding Decision Modeling
- BasicSkill Level
- 4.8+
- 354
Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.
Data Literacy
Course
Gemini in Google Meet
- BasicSkill Level
- 4.9+
- 349
Enhance virtual meetings with Gemini in Google Meet. Leverage AI-driven summaries, notes, and tools to make every meeting more efficient and actionable.
Artificial Intelligence
Data Management
Course
Baseball Data Visualization in Power BI
- BasicSkill Level
- 4.9+
- 345
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
AI-Assisted Product Launch
- BasicSkill Level
- 4.8+
- 341
Analyze market dynamics and craft a strategic entry plan for an EV manufacturer using generative AI.
Artificial Intelligence
Course
Data Fluency
- BasicSkill Level
- 4.8+
- 335
Master data fluency! Learn skills for individuals and organizations, understand behaviors, and build a data-fluent culture.
Data Literacy
Course
Interactive Maps with leaflet in R
- BasicSkill Level
- 4.7+
- 333
Learn how to produce interactive web maps with ease using leaflet.
Data Visualization
Course
AI-Assisted Restaurant Planning
- BasicSkill Level
- 4.8+
- 326
Interact with a customized GPT and use your prompting skills to plan and open your restaurant.
Artificial Intelligence
Course
Building Marketing Workflows with n8n
- BasicSkill Level
- 4.9+
- 314
Build marketing workflows in n8n using AI agents. Automate campaign strategy, conversion optimization, and lead generation from scratch.
Artificial Intelligence
Course
Introduction to Databricks Lakehouse
- BasicSkill Level
- 4.8+
- 310
Explore the Databricks Lakehouse - from medallion architecture and clusters to governance, sharing, and deployment.
Data Engineering
Course
Introduction to DataLab
- BasicSkill Level
- 4.9+
- 309
Learn the fundamentals of using DataLab, an AI-powered data notebook for data analysis and exploration.
Reporting
Course
Introduction to Portfolio Analysis in R
- BasicSkill Level
- 4.8+
- 304
Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.
Applied Finance
Course
Categorical Data in the Tidyverse
- BasicSkill Level
- 4.8+
- 303
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
Plan and Implement a Data Analytics Environment with Microsoft Fabric
- BasicSkill Level
- 4.8+
- 300
Learn how to set up and manage your Microsoft Fabric infrastructure.
Other
Course
Case Study: Exploratory Data Analysis in R
- BasicSkill Level
- 4.9+
- 272
Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.
Exploratory Data Analysis
Course
Exploring Data Transformation with Google Cloud
- BasicSkill Level
- 4.9+
- 268
Exploring Data Transformation with Google Cloud
Cloud
Course
Gen AI Apps: Transform Your Work
- BasicSkill Level
- 4.8+
- 263
This course introduces Google’s gen AI applications, such as Google Workspace with Gemini and NotebookLM.
Cloud
Course
Data Transformation in KNIME
- BasicSkill Level
- 4.8+
- 257
Enhance your KNIME skills with our course on data transformation, column operations, and workflow optimization.
Data Preparation
Cloud
Course
MLOps for Business
- BasicSkill Level
- 4.9+
- 246
Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.
Machine Learning
Course
Concepts in Computer Science
- BasicSkill Level
- 4.8+
- 245
Learn how computers work, design efficient algorithms, and explore computational theory to solve real-world problems.
Software Development
Course
Introduction to Business Valuation
- BasicSkill Level
- 4.9+
- 240
Learn business valuation with real-world applications and case studies using discounted cash flows (DCF).
Applied Finance
Course
Data Manipulation in KNIME
- BasicSkill Level
- 4.8+
- 225
Automate data manipulation with KNIME, mastering merging, aggregation, database workflows, and advanced file handling.
Data Manipulation
Course
Gen AI: Unlock Foundational Concepts
- BasicSkill Level
- 4.8+
- 215
You unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI.
Cloud
Course
Data Visualization in KNIME
- BasicSkill Level
- 4.8+
- 205
Learn to create compelling data visualizations with KNIME, covering charts, components, and dashboards.
Data Visualization
Course
Building Dashboards with shinydashboard
- BasicSkill Level
- 4.7+
- 203
Learn to create interactive dashboards with R using the powerful shinydashboard package. Create dynamic and engaging visualizations for your audience.
Reporting
Course
Gen AI: Navigate the Landscape
- BasicSkill Level
- 4.8+
- 193
You explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.
Cloud
Course
Quantitative Risk Management in R
- BasicSkill Level
- 4.9+
- 184
Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.
Applied Finance
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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