Course
Text-to-Query Agents with MongoDB and LangGraph
- IntermediateSkill Level
- 4.8+
- 159
Discover how to talk to your data using text-to-query AI agents with MongoDB and LangGraph.
Artificial Intelligence
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Course
Handling Missing Data with Imputations in R
- AdvancedSkill Level
- 4.7+
- 158
Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.
Data Manipulation
Course
Financial Forecasting in Python
- IntermediateSkill Level
- 4.8+
- 155
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
Course
Differential Expression Analysis with limma in R
- AdvancedSkill Level
- 4.8+
- 154
Learn to use the Bioconductor package limma for differential gene expression analysis.
Probability & Statistics
Course
Modernize Infrastructure and Applications with Google Cloud
- BasicSkill Level
- 4.8+
- 153
Modernize Infrastructure and Applications with Google Cloud
Cloud
Course
Structural Equation Modeling with lavaan in R
- AdvancedSkill Level
- 4.8+
- 151
Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.
Probability & Statistics
Course
Cleaning Data in Java
- IntermediateSkill Level
- 4.9+
- 147
Master data cleaning in Java using statistical methods, transformations, and validation for reliable apps.
Importing & Cleaning Data
Course
Analyzing Police Activity with pandas
- IntermediateSkill Level
- 4.8+
- 147
Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.
Data Manipulation
Course
Analyzing US Census Data in Python
- IntermediateSkill Level
- 4.8+
- 146
Learn to use the Census API to work with demographic and socioeconomic data.
Exploratory Data Analysis
Course
Data Transformation with Polars
- IntermediateSkill Level
- 5.0+
- 144
Take Polars further with text manipulation, rolling statistics, DataFrame joins, and advanced analytics.
Data Manipulation
Course
Case Study: Ecommerce Analysis in Tableau
- IntermediateSkill Level
- 4.7+
- 144
In ecommerce, increasing sales and reducing expenses are top priorities. In this case study, youll investigate data from an online pet supply company.
Data Visualization
Course
Python for MATLAB Users
- BasicSkill Level
- 4.8+
- 143
Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.
Software Development
Course
Advanced NLP with spaCy
- IntermediateSkill Level
- 4.6+
- 141
Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.
Machine Learning
Course
R For SAS Users
- BasicSkill Level
- 4.8+
- 139
Learn how to translate your SAS knowledge into R and analyze data using this free and powerful software language.
Software Development
Course
Discrete Event Simulation in Python
- AdvancedSkill Level
- 4.8+
- 139
Discover the power of discrete-event simulation in optimizing your business processes. Learn to develop digital twins using Pythons SimPy package.
Probability & Statistics
Course
Pandas Joins for Spreadsheet Users
- IntermediateSkill Level
- 4.8+
- 138
Learn how to effectively and efficiently join datasets in tabular format using the Python Pandas library.
Data Manipulation
Course
Analyzing Social Media Data in R
- IntermediateSkill Level
- 4.9+
- 136
Extract and visualize Twitter data, perform sentiment and network analysis, and map the geolocation of your tweets.
Data Manipulation
Course
Introduction to Natural Language Processing in R
- IntermediateSkill Level
- 4.8+
- 135
Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.
Machine Learning
Course
Support Vector Machines in R
- IntermediateSkill Level
- 4.9+
- 133
This course will introduce the support vector machine (SVM) using an intuitive, visual approach.
Machine Learning
Machine Learning
Course
Introduction to Databricks Genie
- BasicSkill Level
- 4.8+
- 133
Ask data questions in plain English with Databricks Genie - build spaces, curate business language, and monitor quality.
Data Engineering
Course
Dimensionality Reduction in R
- BasicSkill Level
- 4.8+
- 132
Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.
Machine Learning
Course
Feature Engineering in R
- IntermediateSkill Level
- 4.8+
- 131
Learn the principles of feature engineering for machine learning models and how to implement them using the R tidymodels framework.
Machine Learning
Course
Loan Amortization in Google Sheets
- IntermediateSkill Level
- 4.7+
- 127
Learn how to build an amortization dashboard in Google Sheets with financial and conditional formulas.
Applied Finance
Course
Importing and Managing Financial Data in R
- IntermediateSkill Level
- 4.7+
- 125
Learn how to access financial data from local files as well as from internet sources.
Applied Finance
Course
Foundations of Functional Programming with purrr
- IntermediateSkill Level
- 4.8+
- 124
Learn to easily summarize and manipulate lists using the purrr package.
Software Development
Course
DataLab with SQL
- BasicSkill Level
- 4.8+
- 122
Elevate your analysis with this hands-on course using SQL with DataLab workbooks.
Reporting
Course
Serverless Applications with AWS Lambda
- IntermediateSkill Level
- 4.8+
- 120
Build, deploy, and optimize serverless apps with AWS Lambda. Master event processing, error handling, concurrency, and safe deployments in a live AWS Console.
Cloud
Course
Business Process Analytics in R
- IntermediateSkill Level
- 4.8+
- 118
Learn how to analyze business processes in R and extract actionable insights from enormous sets of event data.
Reporting
Course
Parallel Programming with Dask in Python
- IntermediateSkill Level
- 4.8+
- 118
Learn how to use Python parallel programming with Dask to upscale your workflows and efficiently handle big data.
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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