Course
Transactions and Error Handling in SQL Server
- IntermediateSkill Level
- 4.8+
- 321
Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.
Software Development
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Course
Databricks with the Python SDK
- AdvancedSkill Level
- 4.8+
- 321
Master Databricks with Python: learn to authenticate, manage clusters, automate jobs, and query AI models programmatically.
Artificial Intelligence
Course
Optimizing Code in Java
- AdvancedSkill Level
- 4.8+
- 321
Learn key techniques to optimize Java performance, from algorithm efficiency to JVM tuning and multithreading.
Software Development
Course
Advanced Deep Learning with Keras
- IntermediateSkill Level
- 4.8+
- 317
Learn how to develop deep learning models with Keras.
Artificial Intelligence
Course
Baseball Data Visualization in Power BI
- BasicSkill Level
- 4.9+
- 313
Discover how to analyze and visualize baseball data using Power BI. Create scatter plots, tornado charts, and gauges to bring baseball insights alive.
Data Visualization
Course
Winning a Kaggle Competition in Python
- AdvancedSkill Level
- 4.8+
- 313
Learn how to approach and win competitions on Kaggle.
Machine Learning
Course
Decoding Decision Modeling
- BasicSkill Level
- 4.8+
- 311
Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.
Data Literacy
Course
Introduction to DataLab
- BasicSkill Level
- 4.9+
- 307
Learn the fundamentals of using DataLab, an AI-powered data notebook for data analysis and exploration.
Reporting
Course
Introduction to Python in Power BI
- IntermediateSkill Level
- 4.9+
- 306
Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.
Data Manipulation
Course
Analyzing Survey Data in R
- IntermediateSkill Level
- 4.8+
- 304
Learn survey design using common design structures followed by visualizing and analyzing survey results.
Probability & Statistics
Course
Case Study: Inventory Analysis in Power BI
- IntermediateSkill Level
- 4.8+
- 304
This Power BI case study follows a real-world business use case on tackling inventory analysis using DAX and visualizations.
Data Visualization
Course
Time Series Analysis in Power BI
- IntermediateSkill Level
- 4.8+
- 299
Learn to analyze data over time with this practical course on Time Series Analysis in Power BI. Work with real datasets & practice common techniques.
Data Visualization
Course
Practicing Statistics Interview Questions in Python
- AdvancedSkill Level
- 4.8+
- 299
Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.
Probability & Statistics
Course
Network Analysis in R
- IntermediateSkill Level
- 4.8+
- 296
Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.
Probability & Statistics
Course
GARCH Models in Python
- IntermediateSkill Level
- 4.8+
- 295
Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.
Applied Finance
Course
Exploring Data Transformation with Google Cloud
- BasicSkill Level
- 4.9+
- 291
Exploring Data Transformation with Google Cloud
Cloud
Course
Building Agentic Workflows with LlamaIndex
- AdvancedSkill Level
- 4.7+
- 279
Build AI agentic workflows that can plan, search, remember, and collaborate, using LlamaIndex.
Artificial Intelligence
Course
Marketing Analytics: Predicting Customer Churn in Python
- IntermediateSkill Level
- 4.9+
- 277
Learn how to use Python to analyze customer churn and build a model to predict it.
Exploratory Data Analysis
Course
Case Study: Competitor Sales Analysis in Power BI
- IntermediateSkill Level
- 4.8+
- 274
This Power BI case study follows a real-world business use case where you will apply the concepts of ETL and visualization.
Data Visualization
Course
Introduction to Amazon Bedrock
- IntermediateSkill Level
- 4.8+
- 270
Learn to use Amazon Bedrock to access foundation AI models and build with AI - without managing complex infrastructure.
Artificial Intelligence
Course
Case Study: Data Analysis in Databricks
- AdvancedSkill Level
- 4.6+
- 268
Learn to analyze Airbnb data using SQL in Databricks, create dashboards, and derive actionable insights.
Importing & Cleaning Data
Course
Categorical Data in the Tidyverse
- BasicSkill Level
- 4.8+
- 266
Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.
Data Manipulation
Course
Multi-Modal Models with Hugging Face
- IntermediateSkill Level
- 4.8+
- 265
Combine text, images, audio, and video with the latest AI models from Hugging Face, and generate new images and videos!
Artificial Intelligence
Course
Analyzing Financial Statements in Python
- IntermediateSkill Level
- 4.7+
- 264
Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.
Applied Finance
Course
Introduction to Redshift
- IntermediateSkill Level
- 4.8+
- 257
Master Amazon Redshifts SQL, data management, optimization, and security.
Data Engineering
Course
Hierarchical and Recursive Queries in SQL Server
- AdvancedSkill Level
- 4.8+
- 255
Learn how to write recursive queries and query hierarchical data structures.
Software Development
Course
Cleaning Data in SQL Server Databases
- IntermediateSkill Level
- 4.8+
- 247
Develop the skills you need to clean raw data and transform it into accurate insights.
Data Preparation
Cloud
Course
Advanced Probability: Uncertainty in Data
- AdvancedSkill Level
- 4.8+
- 240
Develop a better intuition for advanced probability, risk assessment, and simulation techniques to make data-driven business decisions with confidence.
Probability & Statistics
Course
Customer Analytics and A/B Testing in Python
- IntermediateSkill Level
- 4.8+
- 237
Learn how to use Python to create, run, and analyze A/B tests to make proactive business decisions.
Probability & Statistics
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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