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779 Courses

Course

Forecasting in R

  • BasicSkill Level
  • 4.8+
  • 56 reviews

Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.

Probability & Statistics

5 hours

Course

Biomedical Image Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 250 reviews

Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.

Data Manipulation

4 hours

Course

Monitoring Machine Learning in Python

  • AdvancedSkill Level
  • 4.8+
  • 414 reviews

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

Machine Learning

3 hours

Course

Introduction to Python in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 165 reviews

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

Data Manipulation

3 hours

Course

Concepts in Computer Science

  • BasicSkill Level
  • 4.7+
  • 194 reviews

Learn how computers work, design efficient algorithms, and explore computational theory to solve real-world problems.

Software Development

3 hours

Course

Case Study: Analyzing Job Market Data in Tableau

  • BasicSkill Level
  • 4.7+
  • 615 reviews

In this case study, you’ll use visualization techniques to find out what skills are most in-demand for data scientists, data analysts, and data engineers.

Data Visualization

3 hours

Course

Cleaning Data in PostgreSQL Databases

  • IntermediateSkill Level
  • 4.8+
  • 488 reviews

Learn to tame your raw, messy data stored in a PostgreSQL database to extract accurate insights.

Data Preparation

4 hours

Course

Improving Your Data Visualizations in Python

  • IntermediateSkill Level
  • 4.7+
  • 334 reviews

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

Data Visualization

4 hours

Course

Case Study: Supply Chain Analytics in Power BI

  • BasicSkill Level
  • 4.8+
  • 207 reviews

Learn how to use Power BI for supply chain analytics in this case study. Create a make vs. buy analysis tool, calculate costs, and analyze production volumes.

Data Visualization

4 hours

Course

Deep Reinforcement Learning in Python

  • AdvancedSkill Level
  • 4.8+
  • 298 reviews

Learn and use powerful Deep Reinforcement Learning algorithms, including refinement and optimization techniques.

Artificial Intelligence

4 hours

Course

Introduction to Power Apps

  • BasicSkill Level
  • 4.7+
  • 20 reviews

Build custom business apps without code using Microsoft Power Apps - from blank canvas to published, responsive app.

Artificial Intelligence

3 hours

Course

Databricks with the Python SDK

  • AdvancedSkill Level
  • 4.8+
  • 100 reviews

Master Databricks with Python: learn to authenticate, manage clusters, automate jobs, and query AI models programmatically.

Artificial Intelligence

3 hours

Course

Life Insurance Products Valuation in R

  • BasicSkill Level
  • 4.8+
  • 55 reviews

Learn the basics of cash flow valuation, work with human mortality data and build life insurance products in R.

Applied Finance

4 hours

Course

Introduction to DataLab

  • BasicSkill Level
  • 4.8+
  • 123 reviews

Learn the fundamentals of using DataLab, an AI-powered data notebook for data analysis and exploration.

Reporting

1 hour

Course

Decoding Decision Modeling

  • BasicSkill Level
  • 4.8+
  • 211 reviews

Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.

Data Literacy

1 hour

Course

AI-Assisted Restaurant Planning

  • BasicSkill Level
  • 4.8+
  • 426 reviews

Interact with a customized GPT and use your prompting skills to plan and open your restaurant.

Artificial Intelligence

1 hour

Course

Manipulating Time Series Data in R

  • IntermediateSkill Level
  • 4.8+
  • 305 reviews

Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.

Data Manipulation

4 hours

Course

Baseball Data Visualization in Power BI

  • BasicSkill Level
  • 4.8+
  • 225 reviews

Discover how to analyze and visualize baseball data using Power BI. Create scatter plots, tornado charts, and gauges to bring baseball insights alive.

Data Visualization

1 hour

Course

Window Functions in Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 582 reviews

Discover Snowflake window functions to solve complex data problems with rankings, partitions, and rolling calculations.

Data Manipulation

3 hours

Course

Introduction to Data Versioning with DVC

  • IntermediateSkill Level
  • 4.7+
  • 434 reviews

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

Machine Learning

3 hours

Course

Introduction to Julia

  • BasicSkill Level
  • 4.8+
  • 142 reviews

Julia is a new programming language designed to be the ideal language for scientific computing, machine learning, and data mining.

Software Development

4 hours

Course

Deploying Applications on AWS

  • IntermediateSkill Level
  • 4.8+
  • 40 reviews

Deploy, secure, and operate apps on AWS with Lambda, API Gateway, Cognito, IAM, CloudWatch, and X-Ray. Hands-on prep for the DVA-C02 exam.

Cloud

3 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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