Course
Introduction to Optimization in Python
- IntermediateSkill Level
- 4.8+
- 688
Learn to solve real-world optimization problems using Pythons SciPy and PuLP, covering everything from basic to constrained and complex optimization.
Software Development
Data, AI, and Cloud Courses
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By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.328 Courses
Course
User-Oriented Design in Power BI
- IntermediateSkill Level
- 4.7+
- 686
Learn how to design Power BI visualizations and reports with users in mind.
Data Visualization
Course
Introduction to Portfolio Risk Management in Python
- IntermediateSkill Level
- 4.8+
- 685
Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.
Applied Finance
Course
Biomedical Image Analysis in Python
- IntermediateSkill Level
- 4.8+
- 683
Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.
Data Manipulation
Course
Dimensionality Reduction in Python
- IntermediateSkill Level
- 4.8+
- 679
Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.
Machine Learning
Course
Credit Risk Modeling in Python
- IntermediateSkill Level
- 4.8+
- 673
Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.
Applied Finance
Course
Statistical Thinking in Python (Part 1)
- IntermediateSkill Level
- 4.9+
- 661
Build the foundation you need to think statistically and to speak the language of your data.
Probability & Statistics
Course
Intermediate Regression with statsmodels in Python
- IntermediateSkill Level
- 4.8+
- 656
Learn to perform linear and logistic regression with multiple explanatory variables.
Probability & Statistics
Course
Working with Geospatial Data in Python
- IntermediateSkill Level
- 4.8+
- 651
This course will show you how to integrate spatial data into your Python Data Science workflow.
Data Manipulation
Course
Linear Algebra for Data Science in R
- IntermediateSkill Level
- 4.7+
- 645
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.
Probability & Statistics
Course
Sentiment Analysis in Python
- IntermediateSkill Level
- 4.8+
- 642
Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.
Machine Learning
Course
Introduction to Text Analysis in R
- IntermediateSkill Level
- 4.8+
- 622
Analyze text data in R using the tidy framework.
Data Manipulation
Course
Natural Language Processing with spaCy
- IntermediateSkill Level
- 4.8+
- 606
Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.
Machine Learning
Course
Market Basket Analysis in Python
- IntermediateSkill Level
- 4.9+
- 580
Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.
Machine Learning
Course
Improving Query Performance in SQL Server
- IntermediateSkill Level
- 4.8+
- 576
In this course, students will learn to write queries that are both efficient and easy to read and understand.
Software Development
Course
Data Types and Functions in Snowflake
- IntermediateSkill Level
- 4.9+
- 575
Learn Snowflake data types and functions to manipulate text, numbers, and dates while building custom functions and pivot tables.
Data Manipulation
Course
Window Functions in Snowflake
- IntermediateSkill Level
- 4.9+
- 566
Discover Snowflake window functions to solve complex data problems with rankings, partitions, and rolling calculations.
Data Manipulation
Course
Financial Trading in Python
- IntermediateSkill Level
- 4.8+
- 564
Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!
Applied Finance
Course
Developing Machine Learning Models for Production
- IntermediateSkill Level
- 4.8+
- 560
Shift to an MLOps mindset, enabling you to train, document, maintain, and scale your machine learning models to their fullest potential.
Machine Learning
Course
String Manipulation with stringr in R
- IntermediateSkill Level
- 4.8+
- 557
Learn how to pull character strings apart, put them back together and use the stringr package.
Software Development
Course
Building Dashboards with Dash and Plotly
- IntermediateSkill Level
- 4.8+
- 550
Learn how to build interactive and insight-rich dashboards with Dash and Plotly.
Data Visualization
Course
Unsupervised Learning in R
- IntermediateSkill Level
- 4.8+
- 550
This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.
Machine Learning
Course
Introduction to Bioconductor in R
- IntermediateSkill Level
- 4.8+
- 545
Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!
Probability & Statistics
Course
Machine Learning with caret in R
- IntermediateSkill Level
- 4.9+
- 541
This course teaches the big ideas in machine learning like how to build and evaluate predictive models.
Machine Learning
Course
Writing Functions and Stored Procedures in SQL Server
- IntermediateSkill Level
- 4.9+
- 531
Master SQL Server programming by learning to create, update, and execute functions and stored procedures.
Software Development
Course
Cleaning Data in PostgreSQL Databases
- IntermediateSkill Level
- 4.8+
- 531
Learn to tame your raw, messy data stored in a PostgreSQL database to extract accurate insights.
Data Preparation
Course
Case Study: Net Revenue Management in Excel
- IntermediateSkill Level
- 4.8+
- 523
You will use Net Revenue Management techniques in Excel for a Fast Moving Consumer Goods company.
Applied Finance
Course
Statistical Techniques in Tableau
- IntermediateSkill Level
- 4.8+
- 519
Take your reporting skills to the next level with Tableau’s built-in statistical functions.
Probability & Statistics
Course
Case Study: Analyzing Healthcare Data in Power BI
- IntermediateSkill Level
- 4.9+
- 518
Practice Power BI with our healthcare case study. Analyze data, uncover efficiency insights, and build a dashboard.
Data Visualization
Course
NoSQL Concepts
- IntermediateSkill Level
- 4.8+
- 513
In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.
Data Engineering
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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