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394 Courses

Course

Developing Applications with Google Cloud: Foundations

  • IntermediateSkill Level
  • 5
  • 12 reviews

You learn best practices for cloud applications, and how to select compute and data options to match your application use cases.

Cloud

6 hours 45 min

Course

Analyzing US Census Data in R

  • IntermediateSkill Level
  • 4.8+
  • 38 reviews

Learn to rapidly visualize and explore demographic data from the United States Census Bureau using tidyverse tools.

Exploratory Data Analysis

4 hours

Course

Parallel Programming in R

  • IntermediateSkill Level
  • 4.7+
  • 79 reviews

Unlock the power of parallel computing in R. Enhance your data analysis skills, speed up computations, and process large datasets effortlessly.

Software Development

4 hours

Course

Pandas Joins for Spreadsheet Users

  • IntermediateSkill Level
  • 4.7+
  • 59 reviews

Learn how to effectively and efficiently join datasets in tabular format using the Python Pandas library.

Data Manipulation

4 hours

Course

Intermediate Portfolio Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 74 reviews

Advance you R finance skills to backtest, analyze, and optimize financial portfolios.

Applied Finance

5 hours

Course

Architecting with Google Kubernetes Engine: Production

  • IntermediateSkill Level
  • 4.8+
  • 16 reviews

Secure and monitor GKE production environments. Learn access control, logging, monitoring, CI/CD pipelines, and managed storage integration on Google Cloud.

Cloud

3 hours 30 min

Course

Building Dashboards with flexdashboard

  • IntermediateSkill Level
  • 4.7+
  • 51 reviews

In this course youll learn how to create static and interactive dashboards using flexdashboard and shiny.

Reporting

4 hours

Course

Case Study: Ecommerce Analysis in Tableau

  • IntermediateSkill Level
  • 4.7+
  • 65 reviews

In ecommerce, increasing sales and reducing expenses are top priorities. In this case study, youll investigate data from an online pet supply company.

Data Visualization

3 hours

Course

Streamline App Development with Gemini Code Assist

  • IntermediateSkill Level
  • 5
  • 12 reviews

This course introduces you to the core features and functionalities of Gemini Code Assist, an AI-powered app development collaborator for Google Cloud.

Cloud

2 hours

Course

Optimizing R Code with Rcpp

  • IntermediateSkill Level
  • 4.8+
  • 14 reviews

Use C++ to dramatically boost the performance of your R code.

Software Development

4 hours

Course

Forecasting Product Demand in R

  • IntermediateSkill Level
  • 4.7+
  • 31 reviews

Learn how to identify important drivers of demand, look at seasonal effects, and predict demand for a hierarchy of products from a real world example.

Probability & Statistics

4 hours

Course

Introduction to Anomaly Detection in R

  • IntermediateSkill Level
  • 4.8+
  • 29 reviews

Learn statistical tests for identifying outliers and how to use sophisticated anomaly scoring algorithms.

Probability & Statistics

4 hours

Course

Introduction to Data Visualization with Julia

  • IntermediateSkill Level
  • 4.7+
  • 34 reviews

Master data visualization in Julia. Learn how to make stunning plots while understanding when and how to use them.

Data Visualization

4 hours

Course

Work with Gemini Models in BigQuery

  • IntermediateSkill Level
  • 4.8+
  • 17 reviews

Work with Gemini AI models in BigQuery for sentiment analysis. Analyze customer reviews using SQL and Python notebooks with Gemini.

Cloud

1 hour

Course

Architecting with Google Kubernetes Engine: Workloads

  • IntermediateSkill Level
  • 4.8+
  • 16 reviews

Deploy and manage Kubernetes workloads on GKE. Cover networking, deployments, jobs, persistent storage, and data management in production environments.

Cloud

2 hours 30 min

Course

Interactive Data Visualization with Bokeh

  • IntermediateSkill Level
  • 4.7+
  • 43 reviews

Learn how to create interactive data visualizations, including building and connecting widgets using Bokeh!

Data Visualization

4 hours

Course

Predicting CTR with Machine Learning in Python

  • IntermediateSkill Level
  • 4.9+
  • 20 reviews

Learn how to predict click-through rates on ads and implement basic machine learning models in Python so that you can see how to better optimize your ads.

Machine Learning

4 hours

Course

Mixture Models in R

  • IntermediateSkill Level
  • 4.7+
  • 28 reviews

Learn mixture models: a convenient and formal statistical framework for probabilistic clustering and classification.

Probability & Statistics

4 hours

Course

Predictive Analytics using Networked Data in R

  • IntermediateSkill Level
  • 4.8+
  • 35 reviews

Learn to predict labels of nodes in networks using network learning and by extracting descriptive features from the network

Probability & Statistics

4 hours

Course

Building Response Models in R

  • IntermediateSkill Level
  • 4.8+
  • 31 reviews

Learn to build simple models of market response to increase the effectiveness of your marketing plans.

Probability & Statistics

4 hours

Course

Retrieval-Augmented Generation with LangChain

  • IntermediateSkill Level
  • 4.7+
  • 89 reviews

Learn to build knowledge-grounded LLM applications that retrieve relevant information from structured and unstructured sources before generating responses.

Artificial Intelligence

AI Tutor

2 hours

Course

LLM Application Fundamentals with LangChain

  • IntermediateSkill Level
  • 4.6+
  • 310 reviews

Learn to build conversational LLM applications — with reliable structured output, persistent conversation history, and real-time streaming.

Artificial Intelligence

AI Tutor

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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