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199 Courses

Course

Improving Your Data Visualizations in Python

  • IntermediateSkill Level
  • 4.7+
  • 293 reviews

Learn to construct compelling and attractive visualizations that help communicate results efficiently and effectively.

Data Visualization

4 hours

Course

Ensemble Methods in Python

  • AdvancedSkill Level
  • 4.8+
  • 405 reviews

Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

Machine Learning

4 hours

Course

Introduction to Python in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 146 reviews

Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.

Data Manipulation

3 hours

Course

Monte Carlo Simulations in Python

  • IntermediateSkill Level
  • 4.7+
  • 161 reviews

Learn to design and run your own Monte Carlo simulations using Python!

Probability & Statistics

4 hours

Course

Case Study: Building Software in Python

  • AdvancedSkill Level
  • 4.7+
  • 287 reviews

Build real-world applications with Python—practice using OOP and software engineering principles to write clean and maintainable code.

Software Development

3 hours

Course

Practicing Statistics Interview Questions in Python

  • AdvancedSkill Level
  • 4.7+
  • 87 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

Dealing with Missing Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 180 reviews

Learn how to identify, analyze, remove and impute missing data in Python.

Data Manipulation

4 hours

Course

Statistical Thinking in Python (Part 2)

  • IntermediateSkill Level
  • 4.8+
  • 250 reviews

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

Probability & Statistics

4 hours

Course

GARCH Models in Python

  • IntermediateSkill Level
  • 4.8+
  • 188 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

Analyzing Financial Statements in Python

  • IntermediateSkill Level
  • 4.7+
  • 111 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

Analyzing IoT Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 107 reviews

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

Data Manipulation

4 hours

Course

Analyzing Social Media Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 32 reviews

In this course, youll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.

Data Manipulation

4 hours

Course

Introduction to Linear Modeling in Python

  • IntermediateSkill Level
  • 4.7+
  • 215 reviews

Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.

Probability & Statistics

4 hours

Course

Machine Learning for Marketing in Python

  • IntermediateSkill Level
  • 4.8+
  • 171 reviews

From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

Machine Learning

4 hours

Course

Python for R Users

  • IntermediateSkill Level
  • 4.7+
  • 79 reviews

This course is for R users who want to get up to speed with Python!

Software Development

5 hours

Course

Generalized Linear Models in Python

  • AdvancedSkill Level
  • 4.7+
  • 144 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

Statistical Simulation in Python

  • IntermediateSkill Level
  • 4.8+
  • 28 reviews

Learn to solve increasingly complex problems using simulations to generate and analyze data.

Probability & Statistics

4 hours

Course

Foundations of Inference in Python

  • AdvancedSkill Level
  • 4.8+
  • 221 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

Python for Spreadsheet Users

  • BasicSkill Level
  • 4.8+
  • 34 reviews

Use your knowledge of common spreadsheet functions and techniques to explore Python!

Software Development

4 hours

Course

Survival Analysis in Python

  • AdvancedSkill Level
  • 4.7+
  • 71 reviews

Use survival analysis to work with time-to-event data and predict survival time.

Probability & Statistics

4 hours

Course

Financial Forecasting in Python

  • IntermediateSkill Level
  • 4.8+
  • 90 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

Discrete Event Simulation in Python

  • AdvancedSkill Level
  • 4.7+
  • 70 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

Python for MATLAB Users

  • BasicSkill Level
  • 4.8+
  • 30 reviews

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

Software Development

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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