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298 Courses

Course

Intermediate R for Finance

  • BasicSkill Level
  • 4.8+
  • 41 reviews

Learn about how dates work in R, and explore the world of if statements, loops, and functions using financial examples.

Applied Finance

5 hours

Course

Building Dashboards with shinydashboard

  • BasicSkill Level
  • 4.7+
  • 79 reviews

Learn to create interactive dashboards with R using the powerful shinydashboard package. Create dynamic and engaging visualizations for your audience.

Reporting

4 hours

Course

Introduction to Business Valuation

  • BasicSkill Level
  • 4.8+
  • 167 reviews

Learn business valuation with real-world applications and case studies using discounted cash flows (DCF).

Applied Finance

3 hours

Course

Categorical Data in the Tidyverse

  • BasicSkill Level
  • 4.7+
  • 174 reviews

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

4 hours

Course

Programming Paradigm Concepts

  • BasicSkill Level
  • 4.8+
  • 137 reviews

Explore a range of programming paradigms, including imperative and declarative, procedural, functional, and object-oriented programming.

Software Development

2 hours

Course

Google: Human-Centered AI

  • BasicSkill Level
  • 4.9+
  • 44 reviews

Learn human-centric AI orchestration. Distinguish between augmentation and automation, and balance machine efficiency with human intuition.

Cloud

10 min

Course

Communicating with Data in the Tidyverse

  • BasicSkill Level
  • 4.8+
  • 198 reviews

Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

Data Visualization

4 hours

Course

Google Cloud Fundamentals: Core Infrastructure

  • BasicSkill Level
  • 4.8+
  • 15 reviews

Learn Google Cloud essentials including computing, storage, networking, and resource management through videos and hands-on labs in this foundational course.

Cloud

5 hours

Course

Quantitative Risk Management in R

  • BasicSkill Level
  • 4.8+
  • 83 reviews

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

Applied Finance

5 hours

Course

Google: Introduction to Generative AI

  • BasicSkill Level
  • 4.7+
  • 21 reviews

This is an introductory level course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods.

Cloud

45 min

Course

Python for MATLAB Users

  • BasicSkill Level
  • 4.8+
  • 31 reviews

Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.

Software Development

4 hours

Course

Data Manipulation with data.table in R

  • BasicSkill Level
  • 4.6+
  • 22 reviews

Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.

Data Manipulation

4 hours

Course

Conditional Formatting in Google Sheets

  • BasicSkill Level
  • 4.8+
  • 101 reviews

Learn how to use conditional formatting with your data through built-in options and by creating custom formulas.

Data Manipulation

2 hours

Course

Google Workspace End User: Gmail

  • BasicSkill Level
  • 4.7+
  • 24 reviews

Learn to compose, send, and manage email in Gmail, organize messages with labels, and configure settings like filters and signatures.

Cloud

7 hours 15 min

Course

Data Transformation in KNIME

  • BasicSkill Level
  • 4.8+
  • 287 reviews

Enhance your KNIME skills with our course on data transformation, column operations, and workflow optimization.

Data Preparation

2 hours

Course

Conquering Data Bias

  • BasicSkill Level
  • 4.7+
  • 225 reviews

Unlock your datas potential by learning to detect and mitigate bias for precise analysis and reliable models.

Data Management

2 hours

Course

Case Study: Sales Analytics with Databricks Genie

  • BasicSkill Level
  • 4.9+
  • 15 reviews

Build a Databricks Genie space end-to-end: descriptions, synonyms, instructions, table relationships, example queries, monitoring, and benchmarks.

Data Engineering

2 hours

Course

Working with DeepSeek in Python

  • BasicSkill Level
  • 4.7+
  • 104 reviews

Discover what all of the DeepSeek hype was really about! Build applications using DeepSeeks R1 and V3 models.

Artificial Intelligence

3 hours

Course

Data Visualization in KNIME

  • BasicSkill Level
  • 4.8+
  • 200 reviews

Learn to create compelling data visualizations with KNIME, covering charts, components, and dashboards.

Data Visualization

2 hours

Course

R For SAS Users

  • BasicSkill Level
  • 4.7+
  • 28 reviews

Learn how to translate your SAS knowledge into R and analyze data using this free and powerful software language.

Software Development

4 hours

Course

MLOps for Business

  • BasicSkill Level
  • 4.8+
  • 151 reviews

Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.

Machine Learning

3 hours

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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