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670 Courses

Course

Data Processing in Shell

  • IntermediateSkill Level
  • 4.6+
  • 584

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

Data Manipulation

4 hours

Course

Understanding Digital Transformation

  • BasicSkill Level
  • 4.6+
  • 584

Dive into the world of digital transformation and equip yourself to be an agent of change in a rapidly evolving digital landscape.

Data Literacy

1 hour

Course

Demystifying Decision Science

  • BasicSkill Level
  • 4.6+
  • 583

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

Data Literacy

1 hour

Course

Microsoft Copilot in PowerPoint

  • BasicSkill Level
  • 4.5+
  • 577

Build PowerPoint presentations with Microsoft Copilot. Turn documents into slides, generate visuals, and speaker notes.

Artificial Intelligence

2 hours

Course

Microsoft Copilot in Word

  • BasicSkill Level
  • 4.6+
  • 576

Master Microsoft Copilot in Word to write faster, understand documents instantly, and collaborate more effectively.

Artificial Intelligence

3 hours

Course

Introduction to TensorFlow in Python

  • IntermediateSkill Level
  • 4.3+
  • 572

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

Machine Learning

4 hours

Course

Data Ingestion and Semantic Models with Microsoft Fabric

  • BasicSkill Level
  • 4.6+
  • 565

Learn to bring data into Microsoft Fabric, covering Pipelines, Dataflows, Shortcuts, Semantic Models, security, and model refresh.

Other

4 hours

Course

Input/Output and Streams in Java

  • IntermediateSkill Level
  • 4.5+
  • 564

Advance your Java skills by learning to handle files, process data, and build clean, reusable code using real-world techniques.

Software Development

4 hours

Course

Biomedical Image Analysis in Python

  • IntermediateSkill Level
  • 4.6+
  • 558

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

Data Manipulation

4 hours

Course

Natural Language Processing with spaCy

  • IntermediateSkill Level
  • 4.6+
  • 556

Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.

Machine Learning

4 hours

Course

AI Agents with Hugging Face smolagents

  • AdvancedSkill Level
  • 4.7+
  • 555

Learn how to build intelligent agents that reason, act, and solve real-world tasks using Python.

Artificial Intelligence

3 hours

Course

Building a Go-To-Market Strategy

  • BasicSkill Level
  • 4.4+
  • 552

Create a go-to-market strategy with generative AI: target industries, generate leads, and optimize website keywords.

Artificial Intelligence

1 hour

Course

Cleaning Data in PostgreSQL Databases

  • IntermediateSkill Level
  • 4.7+
  • 551

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

Data Preparation

4 hours

Course

Writing Functions and Stored Procedures in SQL Server

  • IntermediateSkill Level
  • 4.6+
  • 550

Master SQL Server programming by learning to create, update, and execute functions and stored procedures.

Software Development

4 hours

Course

Developing Machine Learning Models for Production

  • IntermediateSkill Level
  • 4.6+
  • 549

Shift to an MLOps mindset, enabling you to train, document, maintain, and scale your machine learning models to their fullest potential.

Machine Learning

4 hours

Course

Quantitative Risk Management in Python

  • AdvancedSkill Level
  • 4.7+
  • 547

Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.

Applied Finance

4 hours

Course

NoSQL Concepts

  • IntermediateSkill Level
  • 4.6+
  • 544

In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.

Data Engineering

2 hours

Course

Sentiment Analysis in Python

  • IntermediateSkill Level
  • 4.5+
  • 541

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

Feature Engineering for NLP in Python

  • AdvancedSkill Level
  • 4.7+
  • 537

Learn techniques to extract useful information from text and process them into a format suitable for machine learning.

Machine Learning

4 hours

Course

Bayesian Data Analysis in Python

  • IntermediateSkill Level
  • 4.6+
  • 535

Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!

Probability & Statistics

4 hours

Course

Improving Query Performance in PostgreSQL

  • IntermediateSkill Level
  • 4.6+
  • 530

Learn how to structure your PostgreSQL queries to run in a fraction of the time.

Software Development

4 hours

Course

ARIMA Models in R

  • BasicSkill Level
  • 4.6+
  • 529

Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

Probability & Statistics

4 hours

Course

Math for Finance Professionals

  • BasicSkill Level
  • 4.8+
  • 527

Learn essential finance math skills with practical Excel exercises and real-world examples.

Applied Finance

3 hours

Course

Importing and Managing Financial Data in Python

  • IntermediateSkill Level
  • 4.6+
  • 526

In this course, youll learn how to import and manage financial data in Python using various tools and sources.

Applied Finance

5 hours

Course

Case Study: Net Revenue Management in Excel

  • IntermediateSkill Level
  • 4.5+
  • 526

You will use Net Revenue Management techniques in Excel for a Fast Moving Consumer Goods company.

Applied Finance

4 hours

Course

Supervised Learning in R: Regression

  • IntermediateSkill Level
  • 4.5+
  • 522

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

Foundations of PySpark

  • IntermediateSkill Level
  • 4.6+
  • 521

Learn to implement distributed data management and machine learning in Spark using the PySpark package.

Data Engineering

4 hours

Course

Case Study: Supply Chain Analytics in Power BI

  • IntermediateSkill Level
  • 4.6+
  • 520

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

Introduction to GCP

  • BasicSkill Level
  • 4.6+
  • 515

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

Cloud

2 hours

Course

String Manipulation with stringr in R

  • IntermediateSkill Level
  • 4.4+
  • 513

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

Software Development

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.