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397 Courses

Course

Building AI Agents with Haystack

  • IntermediateSkill Level
  • 4.8+
  • 45 reviews

Create a healthcare AI agent using Haystack, an open-source framework for orchestrating LLMs and external components.

Artificial Intelligence

1 hour 30 min

Course

Credit Risk Modeling in R

  • IntermediateSkill Level
  • 4.7+
  • 87 reviews

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

Applied Finance

4 hours

Course

Financial Forecasting in Python

  • IntermediateSkill Level
  • 4.8+
  • 92 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

A/B Testing in R

  • IntermediateSkill Level
  • 4.8+
  • 93 reviews

Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.

Probability & Statistics

4 hours

Course

HR Analytics: Exploring Employee Data in R

  • IntermediateSkill Level
  • 4.8+
  • 40 reviews

Learn how to manipulate, visualize, and perform statistical tests through a series of HR analytics case studies.

Exploratory Data Analysis

5 hours

Course

Analyzing Police Activity with pandas

  • IntermediateSkill Level
  • 4.8+
  • 28 reviews

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

Data Manipulation

4 hours

Course

Developing R Packages

  • IntermediateSkill Level
  • 4.7+
  • 153 reviews

Learn to develop R packages and boost your coding skills. Discover package creation benefits, practice with dev tools, and create a unit conversion package.

Software Development

4 hours

Course

Time Series Analysis in Tableau

  • IntermediateSkill Level
  • 4.7+
  • 159 reviews

In this course, you’ll learn to classify, treat and analyze time series; an absolute must, if you’re serious about stepping up as an analytics professional.

Data Visualization

2 hours

Course

Essential Google Cloud Infrastructure: Core Services

  • IntermediateSkill Level
  • 4.9+
  • 30 reviews

This course introduces the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Core Services.

Cloud

8 hours 15 min

Course

Time Series Analysis in PostgreSQL

  • IntermediateSkill Level
  • 4.8+
  • 93 reviews

Learn how to use PostgreSQL to handle time series analysis effectively and apply these techniques to real-world data.

Data Manipulation

4 hours

Course

Bond Valuation and Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 89 reviews

Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.

Applied Finance

4 hours

Course

Fraud Detection in R

  • IntermediateSkill Level
  • 4.7+
  • 38 reviews

Learn to detect fraud with analytics in R.

Machine Learning

4 hours

Course

Intermediate Portfolio Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 70 reviews

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

Applied Finance

5 hours

Course

Case Study: Financial Analysis in KNIME

  • IntermediateSkill Level
  • 4.8+
  • 118 reviews

Apply financial analysis in KNIME with real-world data, enhancing data preparation and workflow skills.

Applied Finance

3 hours

Course

Google: Optimize Agent Behavior

  • IntermediateSkill Level
  • 4.8+
  • 26 reviews

Turn a basic AI agent into a sophisticated assistant using advanced instructions, model selection, planning capabilities, and structured output.

Cloud

2 hours

Course

Case Study: Supply Chain Analytics in Tableau

  • IntermediateSkill Level
  • 4.7+
  • 72 reviews

Dive into our Tableau case study on supply chain analytics. Tackle shipment, inventory management, and dashboard creation to drive business improvements.

Data Visualization

4 hours

Course

Getting Started with Google Kubernetes Engine

  • IntermediateSkill Level
  • 4.8+
  • 26 reviews

The goal of this course is to introduce the basics of Google Kubernetes Engine, or GKE, and how to get applications containerized and running in Google Cloud.

Cloud

5 hours 15 min

Course

Google DeepMind: Fine-Tune Your Model

  • IntermediateSkill Level
  • 4.7+
  • 17 reviews

Unleash the power of language models with fine-tuning. In this course, you will learn how to adjust a pre-trained model to a specific task.

Cloud

8 hours

Course

Analyzing US Census Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 62 reviews

Learn to use the Census API to work with demographic and socioeconomic data.

Exploratory Data Analysis

5 hours

Course

Programming with dplyr

  • IntermediateSkill Level
  • 4.8+
  • 50 reviews

Learn how to perform advanced dplyr transformations and incorporate dplyr and ggplot2 code in functions.

Data Manipulation

4 hours

Course

Feature Engineering in R

  • IntermediateSkill Level
  • 4.7+
  • 152 reviews

Learn the principles of feature engineering for machine learning models and how to implement them using the R tidymodels framework.

Machine Learning

4 hours

Course

Google: Manage Agent Memory and State

  • IntermediateSkill Level
  • 4.6+
  • 24 reviews

Build stateful AI agents that maintain context and remember user preferences using session state, memory management, and personalization.

Cloud

1 hour 30 min

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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