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794 Courses

Course

Dealing With Missing Data in R

  • BasicSkill Level
  • 4.8+
  • 186 reviews

Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

Data Preparation

4 hours

Course

Cleaning Data with PySpark

  • AdvancedSkill Level
  • 4.7+
  • 556 reviews

Learn how to clean data with Apache Spark in Python.

Data Preparation

4 hours

Course

Time Series Analysis in SQL Server

  • IntermediateSkill Level
  • 4.7+
  • 480 reviews

Explore ways to work with date and time data in SQL Server for time series analysis

Data Manipulation

5 hours

Course

Monitoring Machine Learning Concepts

  • IntermediateSkill Level
  • 4.8+
  • 593 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

Data Transformation in Alteryx

  • BasicSkill Level
  • 4.8+
  • 870 reviews

Unlock Alteryx for data transformation, mastering Crosstab, Transpose, and workflow optimization in this interactive course.

Data Manipulation

2 hours

Course

Visualization Best Practices in R

  • BasicSkill Level
  • 4.8+
  • 371 reviews

Learn to effectively convey your data with an overview of common charts, alternative visualization types, and perception-driven style enhancements.

Data Visualization

1 hour

Course

Calculations in Tableau

  • AdvancedSkill Level
  • 4.7+
  • 775 reviews

In this interactive course, you’ll learn how to use functions for your Tableau calculations and when you should use them!

Data Visualization

6 hours

Course

Google: Build and Deploy Agents in Production

  • IntermediateSkill Level
  • 4.7+
  • 164 reviews

Explore multi-agent system architecture and deployment using Googles ADK and Google Cloud infrastructure for production-grade agent applications.

Cloud

30 min

Course

Machine Learning for Finance in Python

  • IntermediateSkill Level
  • 4.8+
  • 253 reviews

Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

Machine Learning

4 hours

Course

Working with Geospatial Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 306 reviews

This course will show you how to integrate spatial data into your Python Data Science workflow.

Data Manipulation

4 hours

Course

Hyperparameter Tuning in Python

  • IntermediateSkill Level
  • 4.8+
  • 900 reviews

Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.

Machine Learning

4 hours

Course

Introduction to Power Apps

  • BasicSkill Level
  • 4.7+
  • 30 reviews

Build custom business apps without code using Microsoft Power Apps - from blank canvas to published, responsive app.

Artificial Intelligence

3 hours

Course

Building a Go-To-Market Strategy

  • BasicSkill Level
  • 4.7+
  • 473 reviews

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

Artificial Intelligence

1 hour

Course

Transactions and Error Handling in SQL Server

  • IntermediateSkill Level
  • 4.8+
  • 369 reviews

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

Software Development

4 hours

Course

Understanding Digital Transformation

  • BasicSkill Level
  • 4.8+
  • 665 reviews

Dive into the world of digital transformation and equip yourself to be an agent of change in a rapidly evolving digital landscape.

Data Literacy

1 hour

Course

Building Data Pipelines with Airflow

  • AdvancedSkill Level
  • 4.8+
  • 65 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

Google: Human-Centered AI

  • BasicSkill Level
  • 4.8+
  • 196 reviews

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

Cloud

10 min

Course

Case Study: Analyzing Job Market Data in Power BI

  • BasicSkill Level
  • 4.8+
  • 380 reviews

Help a fictional company in this interactive Power BI case study. You’ll use Power Query, DAX, and dashboards to identify the most in-demand data jobs!

Data Manipulation

4 hours

Course

Power BI for End Users

  • BasicSkill Level
  • 4.7+
  • 389 reviews

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

Reporting

1 hour

Course

Machine Learning with PySpark

  • AdvancedSkill Level
  • 4.8+
  • 799 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

AI-Assisted Travel Planning

  • BasicSkill Level
  • 4.8+
  • 580 reviews

Master travel planning with WanderBot: craft prompts, build confidence, and streamline your next adventure.

Artificial Intelligence

1 hour

Course

Intermediate Importing Data in R

  • IntermediateSkill Level
  • 4.8+
  • 313 reviews

Parse data in any format. Whether its flat files, statistical software, databases, or data right from the web.

Data Preparation

3 hours

Course

Gemini in Google Drive

  • BasicSkill Level
  • 4.8+
  • 343 reviews

Organize and manage files with Gemini in Google Drive. Use AI-powered search to quickly find information, streamline collaboration, and boost productivity.

Artificial Intelligence

30 min

Course

ARIMA Models in Python

  • AdvancedSkill Level
  • 4.8+
  • 461 reviews

Learn about ARIMA models in Python and become an expert in time series analysis.

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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