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69 Courses

Course

Machine Learning with Tree-Based Models in R

  • BasicSkill Level
  • 4.8+
  • 257 reviews

Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.

Machine Learning

4 hours

Course

Unsupervised Learning in R

  • IntermediateSkill Level
  • 4.7+
  • 100 reviews

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Machine Learning

4 hours

Course

Introduction to TensorFlow in Python

  • IntermediateSkill Level
  • 4.8+
  • 53 reviews

Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.

Machine Learning

4 hours

Course

Supervised Learning in R: Regression

  • IntermediateSkill Level
  • 4.6+
  • 99 reviews

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

Machine Learning

4 hours

Course

Cluster Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 69 reviews

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

Machine Learning

4 hours

Course

Machine Learning with caret in R

  • IntermediateSkill Level
  • 4.8+
  • 42 reviews

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

Machine Learning

4 hours

Course

Fully Automated MLOps

  • IntermediateSkill Level
  • 4.8+
  • 322 reviews

Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

Machine Learning

4 hours

Course

Ensemble Methods in Python

  • AdvancedSkill Level
  • 4.8+
  • 388 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

Monitoring Machine Learning in Python

  • AdvancedSkill Level
  • 4.8+
  • 344 reviews

This course covers everything you need to know to build a basic machine learning monitoring system in Python

Machine Learning

3 hours

Course

ARIMA Models in Python

  • AdvancedSkill Level
  • 4.8+
  • 394 reviews

Learn about ARIMA models in Python and become an expert in time series analysis.

Machine Learning

4 hours

Course

Introduction to Data Versioning with DVC

  • IntermediateSkill Level
  • 4.7+
  • 377 reviews

Explore Data Version Control for ML data management. Master setup, automate pipelines, and evaluate models seamlessly.

Machine Learning

3 hours

Course

Market Basket Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 259 reviews

Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.

Machine Learning

4 hours

Course

Modeling with tidymodels in R

  • IntermediateSkill Level
  • 4.8+
  • 173 reviews

Learn to streamline your machine learning workflows with tidymodels.

Machine Learning

4 hours

Course

Building Chatbots in Python

  • IntermediateSkill Level
  • 4.7+
  • 145 reviews

Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.

Machine Learning

4 hours

Course

Machine Learning for Marketing in Python

  • IntermediateSkill Level
  • 4.8+
  • 168 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

Sentiment Analysis in R

  • IntermediateSkill Level
  • 4.7+
  • 95 reviews

Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.

Machine Learning

4 hours

Course

Fraud Detection in R

  • IntermediateSkill Level
  • 4.7+
  • 37 reviews

Learn to detect fraud with analytics in R.

Machine Learning

4 hours

Course

Machine Learning in the Tidyverse

  • IntermediateSkill Level
  • 4.8+
  • 108 reviews

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

Machine Learning

5 hours

Course

Hyperparameter Tuning in R

  • AdvancedSkill Level
  • 4.8+
  • 54 reviews

Learn how to tune your models hyperparameters to get the best predictive results.

Machine Learning

4 hours

Course

MLOps for Business

  • BasicSkill Level
  • 4.8+
  • 138 reviews

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

Machine Learning

3 hours

Course

Dimensionality Reduction in R

  • BasicSkill Level
  • 4.7+
  • 96 reviews

Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.

Machine Learning

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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