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774 Courses

Course

Machine Learning with PySpark

  • AdvancedSkill Level
  • 4.8+
  • 745 reviews

Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.

Machine Learning

4 hours

Course

Introduction to AWS Boto in Python

  • IntermediateSkill Level
  • 4.8+
  • 226 reviews

Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.

Cloud

4 hours

Course

Demystifying Decision Science

  • BasicSkill Level
  • 4.8+
  • 298 reviews

Solidify your decision science skills by designing data-informed frameworks and implementing efficient solutions.

Data Literacy

1 hour

Course

Building Data Pipelines with Airflow

  • AdvancedSkill Level
  • 4.7+
  • 34 reviews

Author Dags with the TaskFlow API, asset-based scheduling, and deferrable sensors, and run an end-to-end SQL ETL pipeline with quality checks.

Data Engineering

4 hours

Course

Monitoring Machine Learning in Python

  • AdvancedSkill Level
  • 4.8+
  • 396 reviews

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

Machine Learning

3 hours

Course

Streaming Concepts

  • BasicSkill Level
  • 4.7+
  • 535 reviews

Learn about the difference between batching and streaming, scaling streaming systems, and real-world applications.

Data Engineering

2 hours

Course

Develop for Azure Storage

  • IntermediateSkill Level
  • 4.6+
  • 152 reviews

Learn how to store, secure, scale, and process data in Azure using Blob Storage, Cosmos DB, queues, and event-driven services.

Cloud

3 hours

Course

Market Basket Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 284 reviews

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

Machine Learning

4 hours

Course

Working with Geospatial Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 291 reviews

This course will show you how to integrate spatial data into your Python Data Science workflow.

Data Manipulation

4 hours

Course

Data Fluency

  • BasicSkill Level
  • 4.8+
  • 327 reviews

Master data fluency! Learn skills for individuals and organizations, understand behaviors, and build a data-fluent culture.

Data Literacy

2 hours

Course

Foundations of Inference in R

  • IntermediateSkill Level
  • 4.7+
  • 56 reviews

Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

Probability & Statistics

4 hours

Course

Corporate Finance Fundamentals

  • BasicSkill Level
  • 4.8+
  • 245 reviews

Learn key financial concepts such as capital investment, WACC, and shareholder value.

Applied Finance

2 hours

Course

Recommending Skincare Products

  • BasicSkill Level
  • 4.7+
  • 315 reviews

Test a chatbot that matches customers with ideal skincare products using your prompting skills for personalized results.

Artificial Intelligence

1 hour

Course

Data Modeling in Sigma

  • BasicSkill Level
  • 4.8+
  • 129 reviews

Stop rewriting the same joins and calculations, and dive into well-governed, scalable analytics using Sigma data models.

Reporting

2 hours

Course

Azure API Management

  • IntermediateSkill Level
  • 4.7+
  • 129 reviews

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

Cloud

3 hours

Course

Introduction to GCP

  • BasicSkill Level
  • 4.7+
  • 361 reviews

Get to know the Google Cloud Platform (GCP) with this course on storage, data handling, and business modernization using GCP.

Cloud

2 hours

Course

Developing Applications on AWS

  • IntermediateSkill Level
  • 4.9+
  • 25 reviews

Build cloud apps on AWS with API Gateway, Lambda, SQS, SNS, EventBridge, and Kinesis. Master serverless and event-driven patterns for the DVA-C02 exam.

Cloud

3 hours

Course

Data Processing in Shell

  • IntermediateSkill Level
  • 4.8+
  • 531 reviews

Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.

Data Manipulation

4 hours

Course

Introduction to Data Versioning with DVC

  • IntermediateSkill Level
  • 4.7+
  • 420 reviews

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

Machine Learning

3 hours

Course

Sentiment Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 457 reviews

Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.

Machine Learning

4 hours

Course

Databricks with the Python SDK

  • AdvancedSkill Level
  • 4.7+
  • 94 reviews

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

Artificial Intelligence

3 hours

Course

Case Study: Analyzing Job Market Data in Power BI

  • BasicSkill Level
  • 4.8+
  • 341 reviews

Help a fictional company in this interactive Power BI case study. You’ll use Power Query, DAX, and dashboards to identify the most in-demand data jobs!

Data Manipulation

4 hours

Course

Fine-Tuning with Llama 3

  • IntermediateSkill Level
  • 4.7+
  • 408 reviews

Fine-tune Llama for custom tasks using TorchTune, and learn techniques for efficient fine-tuning such as quantization.

Artificial Intelligence

2 hours

Course

AI-Assisted Product Launch

  • BasicSkill Level
  • 4.7+
  • 389 reviews

Analyze market dynamics and craft a strategic entry plan for an EV manufacturer using generative AI.

Artificial Intelligence

1 hour

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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