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778 Courses

Course

Importing and Managing Financial Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 65 reviews

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

Applied Finance

5 hours

Course

Intermediate Power Automate

  • IntermediateSkill Level
  • 4.8+
  • 35 reviews

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

Artificial Intelligence

3 hours

Course

Gemini in Google Meet

  • BasicSkill Level
  • 4.8+
  • 426 reviews

Enhance virtual meetings with Gemini in Google Meet. Leverage AI-driven summaries, notes, and tools to make every meeting more efficient and actionable.

Artificial Intelligence

30 min

Course

Quantitative Risk Management in Python

  • AdvancedSkill Level
  • 4.8+
  • 254 reviews

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

Applied Finance

4 hours

Course

Data Strategy

  • BasicSkill Level
  • 4.7+
  • 1,820 reviews

Master strategic data management for business excellence.

Data Management

1 hour

Course

Building a Go-To-Market Strategy

  • BasicSkill Level
  • 4.7+
  • 453 reviews

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

Artificial Intelligence

1 hour

Course

Snowflake Management, Governance & Collaboration

  • BasicSkill Level
  • 4.8+
  • 200 reviews

Learn to secure, govern, and manage Snowflake at scale. Cover RBAC, data masking, cost monitoring, Time Travel, and secure data sharing.

Data Management

3 hours

Course

Monitoring Machine Learning Concepts

  • IntermediateSkill Level
  • 4.8+
  • 560 reviews

Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.

Machine Learning

2 hours

Course

Gen AI: Navigate the Landscape

  • BasicSkill Level
  • 4.8+
  • 204 reviews

You explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.

Cloud

1 hour 15 min

Course

Machine Learning with PySpark

  • AdvancedSkill Level
  • 4.8+
  • 777 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

Building AI Agents with CrewAI

  • IntermediateSkill Level
  • 4.7+
  • 113 reviews

Build AI teams that work together, automate workflows, and generate content with CrewAI.

Artificial Intelligence

1 hour

Course

Natural Language Processing with spaCy

  • IntermediateSkill Level
  • 4.7+
  • 681 reviews

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

Fully Automated MLOps

  • IntermediateSkill Level
  • 4.8+
  • 389 reviews

Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

Machine Learning

4 hours

Course

Transactions and Error Handling in SQL Server

  • IntermediateSkill Level
  • 4.8+
  • 358 reviews

Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.

Software Development

4 hours

Course

Building Data Pipelines with Airflow

  • AdvancedSkill Level
  • 4.8+
  • 48 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

Data Types and Functions in Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 604 reviews

Learn Snowflake data types and functions to manipulate text, numbers, and dates while building custom functions and pivot tables.

Data Manipulation

3 hours

Course

Power BI for End Users

  • BasicSkill Level
  • 4.7+
  • 376 reviews

Explore Power BI Service, master the interface, make informed decisions, and maximize the power of your reports.

Reporting

1 hour

Course

Azure Compute Solutions

  • IntermediateSkill Level
  • 4.7+
  • 201 reviews

Learn how containers work in Azure, including registries, ACI, AKS basics, scaling, monitoring, and troubleshooting.

Cloud

3 hours

Course

Foundations of Inference in R

  • IntermediateSkill Level
  • 4.7+
  • 58 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

Market Basket Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 303 reviews

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

Machine Learning

4 hours

Course

Developing Applications on AWS

  • IntermediateSkill Level
  • 4.9+
  • 35 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

Demystifying Decision Science

  • BasicSkill Level
  • 4.8+
  • 311 reviews

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

Data Literacy

1 hour

Course

Feature Engineering for NLP in Python

  • IntermediateSkill Level
  • 4.8+
  • 157 reviews

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

Machine Learning

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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