Course
Cleaning Data in R
- IntermediateSkill Level
- 4.8+
- 1.2K
Learn to clean data as quickly and accurately as possible to help you move from raw data to awesome insights.
Data Preparation
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Course
Cluster Analysis in Python
- IntermediateSkill Level
- 4.8+
- 1.1K
In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.
Machine Learning
Course
Experimental Design in Python
- IntermediateSkill Level
- 4.8+
- 1.1K
Implement experimental design setups and perform robust statistical analyses to make precise and valid conclusions!
Probability & Statistics
Course
Introduction to BigQuery
- IntermediateSkill Level
- 4.8+
- 1.1K
Unlock BigQuerys power: grasp its fundamentals, execute queries, and optimize workflows for efficient data analysis.
Data Engineering
Course
Azure App Services
- IntermediateSkill Level
- 4.8+
- 1.1K
Build and deploy scalable web apps and serverless functions in Azure while mastering security, monitoring, and automation.
Cloud
Course
Feature Engineering for Machine Learning in Python
- IntermediateSkill Level
- 4.8+
- 1.1K
Create new features to improve the performance of your Machine Learning models.
Machine Learning
Course
Introduction to Apache Kafka
- IntermediateSkill Level
- 4.8+
- 1.1K
Master Apache Kafka! From core concepts to advanced architecture, learn to create, manage, and troubleshoot Kafka for real-world data streaming challenges!
Data Engineering
Course
Reshaping Data with tidyr
- IntermediateSkill Level
- 4.8+
- 1.1K
Transform almost any dataset into a tidy format to make analysis easier.
Data Manipulation
Course
Introduction to Bash Scripting
- IntermediateSkill Level
- 4.8+
- 1K
Bash scripting allows you to build analytics pipelines in the cloud and work with data stored across multiple files.
Software Development
Course
Intermediate SQL Server
- IntermediateSkill Level
- 4.9+
- 1K
In this course, you will use T-SQL, the flavor of SQL used in Microsofts SQL Server for data analysis.
Software Development
Course
Writing Efficient R Code
- IntermediateSkill Level
- 4.8+
- 1K
Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.
Software Development
Course
Sampling in R
- IntermediateSkill Level
- 4.8+
- 989
Master sampling to get more accurate statistics with less data.
Probability & Statistics
Course
Developing Python Packages
- IntermediateSkill Level
- 4.8+
- 945
Learn to create your own Python packages to make your code easier to use and share with others.
Software Development
Course
Time Series Analysis in R
- IntermediateSkill Level
- 4.9+
- 943
Learn the core techniques necessary to extract meaningful insights from time series data.
Probability & Statistics
Course
Reporting in SQL
- IntermediateSkill Level
- 4.8+
- 901
Learn how to build your own SQL reports and dashboards, plus hone your data exploration, cleaning, and validation skills.
Reporting
Course
Model Validation in Python
- IntermediateSkill Level
- 4.9+
- 885
Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.
Machine Learning
Course
End-to-End Machine Learning
- IntermediateSkill Level
- 4.8+
- 851
Dive into the world of machine learning and discover how to design, train, and deploy end-to-end models.
Machine Learning
Course
Manipulating Time Series Data in R
- IntermediateSkill Level
- 4.8+
- 821
Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.
Data Manipulation
Course
Introduction to Generative AI in Snowflake
- IntermediateSkill Level
- 4.8+
- 815
Learn to build AI applications using Snowflake Cortexs built-in LLM functions for text analysis, generation, and multi-step workflows.
Artificial Intelligence
Course
Data Types and Exceptions in Java
- IntermediateSkill Level
- 4.8+
- 807
Learn to work with Plain Old Java Objects, master the Collections Framework, and handle exceptions like a pro, with logging to back it all up!
Software Development
Course
Hyperparameter Tuning in Python
- IntermediateSkill Level
- 4.9+
- 769
Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.
Machine Learning
Course
A/B Testing in Python
- IntermediateSkill Level
- 4.8+
- 761
Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.
Probability & Statistics
Course
Introduction to MongoDB in Python
- IntermediateSkill Level
- 4.8+
- 759
Learn to manipulate and analyze flexibly structured data with MongoDB.
Data Engineering
Course
Introduction to Databases in Python
- IntermediateSkill Level
- 4.8+
- 739
In this course, youll learn the basics of relational databases and how to interact with them.
Data Manipulation
Course
Machine Learning for Finance in Python
- IntermediateSkill Level
- 4.8+
- 731
Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.
Machine Learning
Course
Software Development with Windsurf
- IntermediateSkill Level
- 4.9+
- 726
Boost your coding with Windsurf, the AI-powered IDE that helps you build, debug, and deploy faster.
Artificial Intelligence
Course
Reporting with R Markdown
- IntermediateSkill Level
- 4.8+
- 719
R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.
Reporting
Course
Input/Output and Streams in Java
- IntermediateSkill Level
- 4.8+
- 714
Advance your Java skills by learning to handle files, process data, and build clean, reusable code using real-world techniques.
Software Development
Course
Modeling with Data in the Tidyverse
- IntermediateSkill Level
- 4.9+
- 704
Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.
Probability & Statistics
Course
Building Web Applications with Shiny in R
- IntermediateSkill Level
- 4.8+
- 692
Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.
Software Development
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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