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778 Courses

Course

Financial Analytics in Google Sheets

  • BasicSkill Level
  • 4.7+
  • 139 reviews

Learn how to build a graphical dashboard with Google Sheets to track the performance of financial securities.

Applied Finance

4 hours

Course

Fundamentals of Bayesian Data Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 233 reviews

Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.

Probability & Statistics

4 hours

Course

Statistical Thinking in Python (Part 2)

  • IntermediateSkill Level
  • 4.7+
  • 268 reviews

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

Probability & Statistics

4 hours

Course

Cleaning Data in SQL Server Databases

  • IntermediateSkill Level
  • 4.8+
  • 212 reviews

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

Data Preparation

4 hours

Course

Using Data Stores in AWS

  • IntermediateSkill Level
  • 4.7+
  • 50 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: Data Analysis in Databricks

  • AdvancedSkill Level
  • 4.6+
  • 99 reviews

Learn to analyze Airbnb data using SQL in Databricks, create dashboards, and derive actionable insights.

Importing & Cleaning Data

3 hours

Course

Analyzing Social Media Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 34 reviews

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

Data Manipulation

4 hours

Course

Google: Human-Centered AI

  • BasicSkill Level
  • 4.8+
  • 96 reviews

Learn human-centric AI orchestration. Distinguish between augmentation and automation, and balance machine efficiency with human intuition.

Cloud

10 min

Course

ARIMA Models in R

  • BasicSkill Level
  • 4.8+
  • 332 reviews

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

Probability & Statistics

4 hours

Course

Ensemble Methods in Python

  • AdvancedSkill Level
  • 4.8+
  • 434 reviews

Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

Machine Learning

4 hours

Course

Introduction to Security Principles in Cloud Computing

  • IntermediateSkill Level
  • 4.8+
  • 12 reviews

In this course, you’ll explore the essentials of cybersecurity, including the security lifecycle, digital transformation, and key cloud computing concepts.

Cloud

18 hours 15 min

Course

Generalized Linear Models in R

  • IntermediateSkill Level
  • 4.8+
  • 214 reviews

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

Probability & Statistics

4 hours

Course

Financial Forecasting in Python

  • IntermediateSkill Level
  • 4.8+
  • 98 reviews

Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.

Applied Finance

4 hours

Course

Case Study: Inventory Analysis in Power BI

  • IntermediateSkill Level
  • 4.7+
  • 184 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

Google Cloud Fundamentals: Core Infrastructure

  • BasicSkill Level
  • 4.9+
  • 36 reviews

Learn Google Cloud essentials including computing, storage, networking, and resource management through videos and hands-on labs in this foundational course.

Cloud

5 hours

Course

Spoken Language Processing in Python

  • IntermediateSkill Level
  • 4.8+
  • 303 reviews

Learn how to load, transform, and transcribe speech from raw audio files in Python.

Data Manipulation

4 hours

Course

Introduction to Linear Modeling in Python

  • IntermediateSkill Level
  • 4.7+
  • 233 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

Anomaly Detection in Python

  • IntermediateSkill Level
  • 4.8+
  • 183 reviews

Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.

Probability & Statistics

4 hours

Course

Case Study: Exploratory Data Analysis in R

  • BasicSkill Level
  • 4.9+
  • 50 reviews

Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

Exploratory Data Analysis

4 hours

Course

Machine Learning with caret in R

  • IntermediateSkill Level
  • 4.8+
  • 46 reviews

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

Machine Learning

4 hours

Course

Python for Spreadsheet Users

  • BasicSkill Level
  • 4.8+
  • 36 reviews

Use your knowledge of common spreadsheet functions and techniques to explore Python!

Software Development

4 hours

Course

Feature Engineering with PySpark

  • AdvancedSkill Level
  • 4.8+
  • 314 reviews

Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.

Data Manipulation

4 hours

Course

Google: Introduction to Large Language Models

  • BasicSkill Level
  • 4.9+
  • 37 reviews

This is an introductory level course that explores what large language models (LLM) are, their use cases, and how you can prompt them.

Cloud

1 hour

Course

Introduction to Amazon Bedrock

  • IntermediateSkill Level
  • 4.7+
  • 136 reviews

Learn to use Amazon Bedrock to access foundation AI models and build with AI - without managing complex infrastructure.

Artificial Intelligence

3 hours

Course

Monitoring and Troubleshooting AWS

  • IntermediateSkill Level
  • 4.8+
  • 22 reviews

Monitor and troubleshoot AWS apps with Amazon CloudWatch and AWS X-Ray. Collect metrics and logs, build dashboards, set alarms, and trace requests.

Cloud

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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