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778 Courses

Course

ARIMA Models in R

  • BasicSkill Level
  • 4.8+
  • 318 reviews

Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

Probability & Statistics

4 hours

Course

Writing Efficient Code with pandas

  • IntermediateSkill Level
  • 4.7+
  • 160 reviews

Learn efficient techniques in pandas to optimize your Python code.

Software Development

4 hours

Course

Google: Human-Centered AI

  • BasicSkill Level
  • 4.9+
  • 48 reviews

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

Cloud

10 min

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

Google: Deploy Your First Agent

  • IntermediateSkill Level
  • 4.9+
  • 22 reviews

Deploy ADK agents to production using Vertex AI Agent Engine and Cloud Run. Add persistent cross-session memory with Memory Bank.

Cloud

1 hour

Course

Error and Uncertainty in Google Sheets

  • IntermediateSkill Level
  • 4.7+
  • 155 reviews

Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.

Probability & Statistics

4 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

Categorical Data in the Tidyverse

  • BasicSkill Level
  • 4.8+
  • 175 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+
  • 140 reviews

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

Software Development

2 hours

Course

Machine Learning in the Tidyverse

  • IntermediateSkill Level
  • 4.8+
  • 117 reviews

Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

Machine Learning

5 hours

Course

Marketing Analytics in Google Sheets

  • IntermediateSkill Level
  • 4.8+
  • 225 reviews

Learn how to ensure clean data entry and build dynamic dashboards to display your marketing data.

Reporting

4 hours

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

Analyzing IoT Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 111 reviews

Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.

Data Manipulation

4 hours

Course

Introduction to Scala

  • IntermediateSkill Level
  • 4.8+
  • 141 reviews

Begin your journey with Scala, a popular language for scalable applications and data engineering infrastructure.

Software Development

3 hours

Course

Analyzing Financial Statements in Python

  • IntermediateSkill Level
  • 4.7+
  • 114 reviews

Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.

Applied Finance

4 hours

Course

Case Study: Mortgage Trading Analysis in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 285 reviews

In this Power BI case study you’ll play the role of a junior trader, analyzing mortgage trading and enhancing your data modeling and financial analysis skills.

Applied Finance

3 hours

Course

Handling Missing Data with Imputations in R

  • AdvancedSkill Level
  • 4.7+
  • 105 reviews

Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.

Data Manipulation

4 hours

Course

Financial Modeling in Google Sheets

  • IntermediateSkill Level
  • 4.7+
  • 276 reviews

Learn basic business modeling including cash flows, investments, annuities, loan amortization, and more using Google Sheets.

Applied Finance

4 hours

Course

Visualizing Geospatial Data in R

  • IntermediateSkill Level
  • 4.5+
  • 88 reviews

Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

Data Visualization

4 hours

Course

Image Modeling with Keras

  • AdvancedSkill Level
  • 4.8+
  • 91 reviews

Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

Artificial Intelligence

4 hours

Course

Modeling with tidymodels in R

  • IntermediateSkill Level
  • 4.8+
  • 184 reviews

Learn to streamline your machine learning workflows with tidymodels.

Machine Learning

4 hours

Course

End-to-End RAG with Weaviate

  • IntermediateSkill Level
  • 4.6+
  • 20 reviews

Master RAG with Weaviate! Embed text and images for retrieval, and experiment with vector, BM25, and hybrid search.

Artificial Intelligence

2 hours

Course

Discrete Event Simulation in Python

  • AdvancedSkill Level
  • 4.7+
  • 78 reviews

Discover the power of discrete-event simulation in optimizing your business processes. Learn to develop digital twins using Pythons SimPy package.

Probability & Statistics

4 hours

Course

Market Basket Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 95 reviews

Explore association rules in market basket analysis with R by analyzing retail data and creating movie recommendations.

Data Manipulation

4 hours

Course

Foundations of Inference in Python

  • AdvancedSkill Level
  • 4.8+
  • 228 reviews

Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.

Probability & Statistics

4 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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