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775 Courses

Course

Intermediate Network Analysis in Python

  • AdvancedSkill Level
  • 4.8+
  • 89 reviews

Analyze time series graphs, use bipartite graphs, and gain the skills to tackle advanced problems in network analytics.

Probability & Statistics

4 hours

Course

Discrete Event Simulation in Python

  • AdvancedSkill Level
  • 4.7+
  • 80 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

Programming Paradigm Concepts

  • BasicSkill Level
  • 4.8+
  • 146 reviews

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

Software Development

2 hours

Course

Foundations of Inference in Python

  • AdvancedSkill Level
  • 4.8+
  • 231 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

Course

Financial Forecasting in Python

  • IntermediateSkill Level
  • 4.8+
  • 96 reviews

Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.

Applied Finance

4 hours

Course

Visualizing Geospatial Data in R

  • IntermediateSkill Level
  • 4.6+
  • 90 reviews

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

Data Visualization

4 hours

Course

Factor Analysis in R

  • AdvancedSkill Level
  • 4.7+
  • 164 reviews

Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

Probability & Statistics

4 hours

Course

GARCH Models in Python

  • IntermediateSkill Level
  • 4.8+
  • 203 reviews

Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.

Applied Finance

4 hours

Course

Writing Efficient Code with pandas

  • IntermediateSkill Level
  • 4.7+
  • 164 reviews

Learn efficient techniques in pandas to optimize your Python code.

Software Development

4 hours

Course

Support Vector Machines in R

  • IntermediateSkill Level
  • 4.8+
  • 95 reviews

This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

Machine Learning

4 hours

Course

Categorical Data in the Tidyverse

  • BasicSkill Level
  • 4.8+
  • 177 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

Network Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 135 reviews

Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

Probability & Statistics

4 hours

Course

Machine Learning in the Tidyverse

  • IntermediateSkill Level
  • 4.8+
  • 119 reviews

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

Machine Learning

5 hours

Course

Google: Optimize Agent Behavior

  • IntermediateSkill Level
  • 4.8+
  • 39 reviews

Turn a basic AI agent into a sophisticated assistant using advanced instructions, model selection, planning capabilities, and structured output.

Cloud

2 hours

Course

Conquering Data Bias

  • BasicSkill Level
  • 4.7+
  • 239 reviews

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

Data Management

2 hours

Course

Introduction to Security in the World of AI

  • IntermediateSkill Level
  • 4.8+
  • 31 reviews

This course equips security and data protection leaders with strategies to securely manage AI within their organizations.

Cloud

1 hour

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

Case Studies in Statistical Thinking

  • IntermediateSkill Level
  • 4.8+
  • 87 reviews

Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

Probability & Statistics

4 hours

Course

Generalized Linear Models in Python

  • AdvancedSkill Level
  • 4.7+
  • 147 reviews

Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.

Probability & Statistics

5 hours

Course

A/B Testing in R

  • IntermediateSkill Level
  • 4.8+
  • 95 reviews

Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.

Probability & Statistics

4 hours

Course

Practicing Statistics Interview Questions in Python

  • AdvancedSkill Level
  • 4.7+
  • 89 reviews

Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.

Probability & Statistics

4 hours

Course

Analyzing IoT Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 116 reviews

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

Data Manipulation

4 hours

Course

Data Manipulation with data.table in R

  • BasicSkill Level
  • 4.6+
  • 23 reviews

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

Data Manipulation

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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