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778 Courses

Course

Building Recommendation Engines in Python

  • IntermediateSkill Level
  • 4.8+
  • 151 reviews

Learn to build recommendation engines in Python using machine learning techniques.

Machine Learning

4 hours

Course

Google: Introduction to Generative AI

  • BasicSkill Level
  • 4.7+
  • 24 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

Marketing Analytics in Tableau

  • IntermediateSkill Level
  • 4.8+
  • 90 reviews

Master marketing analytics using Tableau. Analyze performance, benchmark metrics, and optimize strategies across channels.

Data Preparation

6 hours

Course

Support Vector Machines in R

  • IntermediateSkill Level
  • 4.8+
  • 93 reviews

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

Machine Learning

4 hours

Course

Google Cloud Fundamentals: Core Infrastructure

  • BasicSkill Level
  • 4.8+
  • 17 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

Credit Risk Modeling in R

  • IntermediateSkill Level
  • 4.7+
  • 87 reviews

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

Applied Finance

4 hours

Course

Financial Forecasting in Python

  • IntermediateSkill Level
  • 4.8+
  • 92 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

Analyzing Police Activity with pandas

  • IntermediateSkill Level
  • 4.8+
  • 28 reviews

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

Data Manipulation

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

Essential Google Cloud Infrastructure: Core Services

  • IntermediateSkill Level
  • 4.9+
  • 31 reviews

This course introduces the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Core Services.

Cloud

8 hours 15 min

Course

Inference for Numerical Data in R

  • AdvancedSkill Level
  • 4.8+
  • 110 reviews

In this course youll learn techniques for performing statistical inference on numerical data.

Probability & Statistics

4 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

Case Study: Sales Analytics with Databricks Genie

  • BasicSkill Level
  • 4.9+
  • 20 reviews

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

Data Engineering

2 hours

Course

Building AI Agents with Haystack

  • IntermediateSkill Level
  • 4.8+
  • 46 reviews

Create a healthcare AI agent using Haystack, an open-source framework for orchestrating LLMs and external components.

Artificial Intelligence

1 hour 30 min

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

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

Survival Analysis in Python

  • AdvancedSkill Level
  • 4.7+
  • 73 reviews

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

Probability & Statistics

4 hours

Course

Visualizing Time Series Data in R

  • IntermediateSkill Level
  • 4.8+
  • 183 reviews

Learn how to visualize time series in R, then practice with a stock-picking case study.

Data Visualization

4 hours

Course

Time Series Analysis in Tableau

  • IntermediateSkill Level
  • 4.7+
  • 160 reviews

In this course, you’ll learn to classify, treat and analyze time series; an absolute must, if you’re serious about stepping up as an analytics professional.

Data Visualization

2 hours

Course

Case Studies in Statistical Thinking

  • IntermediateSkill Level
  • 4.9+
  • 85 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

HR Analytics: Exploring Employee Data in R

  • IntermediateSkill Level
  • 4.8+
  • 40 reviews

Learn how to manipulate, visualize, and perform statistical tests through a series of HR analytics case studies.

Exploratory Data Analysis

5 hours

Course

Time Series Analysis in PostgreSQL

  • IntermediateSkill Level
  • 4.8+
  • 94 reviews

Learn how to use PostgreSQL to handle time series analysis effectively and apply these techniques to real-world data.

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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