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772 Courses

Course

Unsupervised Learning in R

  • IntermediateSkill Level
  • 4.8+
  • 112 reviews

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Machine Learning

4 hours

Course

RNA-Seq with Bioconductor in R

  • IntermediateSkill Level
  • 4.7+
  • 156 reviews

Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

Probability & Statistics

4 hours

Course

Working with Dates and Times in R

  • IntermediateSkill Level
  • 4.8+
  • 102 reviews

Learn the essentials of parsing, manipulating and computing with dates and times in R.

Software Development

4 hours

Course

ARIMA Models in R

  • BasicSkill Level
  • 4.8+
  • 341 reviews

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

Probability & Statistics

4 hours

Course

Survival Analysis in R

  • IntermediateSkill Level
  • 4.7+
  • 223 reviews

Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!

Probability & Statistics

4 hours

Course

Fraud Detection in Python

  • IntermediateSkill Level
  • 4.7+
  • 207 reviews

Learn how to detect fraud using Python.

Machine Learning

4 hours

Course

Machine Learning with caret in R

  • IntermediateSkill Level
  • 4.8+
  • 47 reviews

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

Machine Learning

4 hours

Course

Ensemble Methods in Python

  • AdvancedSkill Level
  • 4.8+
  • 444 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

Generalized Linear Models in R

  • IntermediateSkill Level
  • 4.8+
  • 219 reviews

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

Probability & Statistics

4 hours

Course

Cluster Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 79 reviews

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

Machine Learning

4 hours

Course

Case Study: Mortgage Trading Analysis in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 322 reviews

In this Power BI case study you’ll play the role of a junior trader, analyzing mortgage trading and enhancing your data modeling and financial analysis skills.

Applied Finance

3 hours

Course

Financial Analytics in Google Sheets

  • BasicSkill Level
  • 4.7+
  • 142 reviews

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

Applied Finance

4 hours

Course

Using Data Stores in AWS

  • IntermediateSkill Level
  • 4.7+
  • 60 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

Decoding Decision Modeling

  • BasicSkill Level
  • 4.8+
  • 214 reviews

Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.

Data Literacy

1 hour

Course

Feature Engineering with PySpark

  • AdvancedSkill Level
  • 4.8+
  • 324 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

Case Study: Data Analysis in Databricks

  • AdvancedSkill Level
  • 4.6+
  • 105 reviews

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

Importing & Cleaning Data

3 hours

Course

Google: Introduction to Generative AI

  • BasicSkill Level
  • 4.7+
  • 64 reviews

This is an introductory level course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods.

Cloud

45 min

Course

Building Dashboards with shinydashboard

  • BasicSkill Level
  • 4.7+
  • 93 reviews

Learn to create interactive dashboards with R using the powerful shinydashboard package. Create dynamic and engaging visualizations for your audience.

Reporting

4 hours

Course

Google: Deploy Your First Agent

  • IntermediateSkill Level
  • 4.8+
  • 67 reviews

Deploy ADK agents to production using Vertex AI Agent Engine and Cloud Run. Add persistent cross-session memory with Memory Bank.

Cloud

1 hour

Course

Foundations of Inference in Python

  • AdvancedSkill Level
  • 4.8+
  • 255 reviews

Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.

Probability & Statistics

4 hours

Course

Case Study: Inventory Analysis in Power BI

  • IntermediateSkill Level
  • 4.7+
  • 189 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

Introduction to Business Valuation

  • BasicSkill Level
  • 4.8+
  • 187 reviews

Learn business valuation with real-world applications and case studies using discounted cash flows (DCF).

Applied Finance

3 hours

Course

Programming Paradigm Concepts

  • BasicSkill Level
  • 4.8+
  • 154 reviews

Explore a range of programming paradigms, including imperative and declarative, procedural, functional, and object-oriented programming.

Software Development

2 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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