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397 Courses

Course

Marketing Analytics: Predicting Customer Churn in Python

  • IntermediateSkill Level
  • 4.8+
  • 177 reviews

Learn how to use Python to analyze customer churn and build a model to predict it.

Exploratory Data Analysis

4 hours

Course

Intermediate Power Automate

  • IntermediateSkill Level
  • 4.8+
  • 12 reviews

Build reliable Power Automate cloud flows with triggers, branching, approvals, error handling, and production handover.

Artificial Intelligence

3 hours

Course

String Manipulation with stringr in R

  • IntermediateSkill Level
  • 4.7+
  • 54 reviews

Learn how to pull character strings apart, put them back together and use the stringr package.

Software Development

4 hours

Course

Using Data Stores in AWS

  • IntermediateSkill Level
  • 4.7+
  • 32 reviews

Learn to choose, build with, and secure AWS data stores including DynamoDB and S3 through hands-on console exercises and real-world scenarios.

Cloud

3 hours

Course

Case Study: Ecommerce Analysis in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 206 reviews

In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.

Data Visualization

4 hours

Course

Azure API Management

  • IntermediateSkill Level
  • 4.7+
  • 80 reviews

Learn to create, secure, and manage APIs with Azure API Management through hands-on practice.

Cloud

3 hours

Course

Generative AI Essentials with Snowflake

  • IntermediateSkill Level
  • 4.6+
  • 15 reviews

Build generative AI apps on Snowflake with Cortex LLM functions, prompt engineering, and fine-tuning.

Artificial Intelligence

3 hours

Course

Case Study: Inventory Analysis in Power BI

  • IntermediateSkill Level
  • 4.7+
  • 172 reviews

This Power BI case study follows a real-world business use case on tackling inventory analysis using DAX and visualizations.

Data Visualization

5 hours

Course

Statistical Thinking in Python (Part 2)

  • IntermediateSkill Level
  • 4.7+
  • 256 reviews

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

Probability & Statistics

4 hours

Course

Scalable AI Models with PyTorch Lightning

  • IntermediateSkill Level
  • 4.7+
  • 106 reviews

Streamline your AI projects by building modular models and mastering advanced optimization with PyTorch Lightning!

Artificial Intelligence

3 hours

Course

Introduction to Linear Modeling in Python

  • IntermediateSkill Level
  • 4.7+
  • 223 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

Survival Analysis in R

  • IntermediateSkill Level
  • 4.7+
  • 198 reviews

Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!

Probability & Statistics

4 hours

Course

Dealing with Missing Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 184 reviews

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

Data Manipulation

4 hours

Course

Advanced Data Engineering with Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 21 reviews

Build reliable Snowflake pipelines with DevOps and observability: Git, CI/CD, and Snowflake Trail monitoring.

Data Engineering

3 hours

Course

Generalized Linear Models in R

  • IntermediateSkill Level
  • 4.8+
  • 196 reviews

The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

Probability & Statistics

4 hours

Course

Analyzing Social Media Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 33 reviews

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

Data Manipulation

4 hours

Course

GARCH Models in Python

  • IntermediateSkill Level
  • 4.8+
  • 191 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

Machine Learning with caret in R

  • IntermediateSkill Level
  • 4.8+
  • 43 reviews

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

Machine Learning

4 hours

Course

Essential Google Cloud Infrastructure: Foundation

  • IntermediateSkill Level
  • 4.8+
  • 36 reviews

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

Cloud

4 hours 45 min

Course

Cleaning Data in SQL Server Databases

  • IntermediateSkill Level
  • 4.8+
  • 187 reviews

Develop the skills you need to clean raw data and transform it into accurate insights.

Data Preparation

4 hours

Course

Web Scraping in R

  • IntermediateSkill Level
  • 4.7+
  • 99 reviews

Learn how to efficiently collect and download data from any website using R.

Data Preparation

4 hours

Course

Introduction to Redshift

  • IntermediateSkill Level
  • 4.8+
  • 109 reviews

Master Amazon Redshifts SQL, data management, optimization, and security.

Data Engineering

4 hours

Course

Introduction to Scala

  • IntermediateSkill Level
  • 4.8+
  • 141 reviews

Begin your journey with Scala, a popular language for scalable applications and data engineering infrastructure.

Software Development

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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