Course
Building and Optimizing Triggers in SQL Server
- IntermediateSkill Level
- 4.8+
- 333
Learn how to design and implement triggers in SQL Server using real-world examples.
Software Development
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Course
Case Study: Analyzing City Time Series Data in R
- IntermediateSkill Level
- 4.9+
- 329
Strengthen your knowledge of the topics covered in Manipulating Time Series in R using real case study data.
Probability & Statistics
Course
Transactions and Error Handling in SQL Server
- IntermediateSkill Level
- 4.8+
- 329
Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.
Software Development
Course
Building AI Agents with CrewAI
- IntermediateSkill Level
- 4.8+
- 328
Build AI teams that work together, automate workflows, and generate content with CrewAI.
Artificial Intelligence
Course
Winning a Kaggle Competition in Python
- AdvancedSkill Level
- 4.8+
- 326
Learn how to approach and win competitions on Kaggle.
Machine Learning
Course
Advanced Deep Learning with Keras
- IntermediateSkill Level
- 4.8+
- 324
Learn how to develop deep learning models with Keras.
Artificial Intelligence
Course
Optimizing Code in Java
- AdvancedSkill Level
- 4.8+
- 324
Learn key techniques to optimize Java performance, from algorithm efficiency to JVM tuning and multithreading.
Software Development
Course
Fine-Tuning with Llama 3
- IntermediateSkill Level
- 4.7+
- 324
Fine-tune Llama for custom tasks using TorchTune, and learn techniques for efficient fine-tuning such as quantization.
Artificial Intelligence
Course
Case Study: Ecommerce Analysis in Power BI
- IntermediateSkill Level
- 4.9+
- 322
In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.
Data Visualization
Course
Data Fluency
- BasicSkill Level
- 4.8+
- 322
Master data fluency! Learn skills for individuals and organizations, understand behaviors, and build a data-fluent culture.
Data Literacy
Course
Working with Dates and Times in R
- IntermediateSkill Level
- 4.8+
- 322
Learn the essentials of parsing, manipulating and computing with dates and times in R.
Software Development
Course
Object-Oriented Programming with S3 and R6 in R
- AdvancedSkill Level
- 4.8+
- 318
Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.
Software Development
Course
Introduction to Data Versioning with DVC
- IntermediateSkill Level
- 4.8+
- 318
Explore Data Version Control for ML data management. Master setup, automate pipelines, and evaluate models seamlessly.
Machine Learning
Course
AI-Assisted Product Launch
- BasicSkill Level
- 4.8+
- 317
Analyze market dynamics and craft a strategic entry plan for an EV manufacturer using generative AI.
Artificial Intelligence
Course
Introduction to Python in Power BI
- IntermediateSkill Level
- 4.9+
- 315
Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.
Data Manipulation
Course
Baseball Data Visualization in Power BI
- BasicSkill Level
- 4.9+
- 314
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
Inference for Numerical Data in R
- AdvancedSkill Level
- 4.9+
- 314
In this course youll learn techniques for performing statistical inference on numerical data.
Probability & Statistics
Course
Decoding Decision Modeling
- BasicSkill Level
- 4.8+
- 312
Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.
Data Literacy
Course
Introduction to DataLab
- BasicSkill Level
- 4.9+
- 311
Learn the fundamentals of using DataLab, an AI-powered data notebook for data analysis and exploration.
Reporting
Course
GARCH Models in Python
- IntermediateSkill Level
- 4.8+
- 308
Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.
Applied Finance
Course
Time Series Analysis in Power BI
- IntermediateSkill Level
- 4.8+
- 308
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
Case Study: Inventory Analysis in Power BI
- IntermediateSkill Level
- 4.8+
- 307
This Power BI case study follows a real-world business use case on tackling inventory analysis using DAX and visualizations.
Data Visualization
Course
Analyzing Survey Data in R
- IntermediateSkill Level
- 4.8+
- 303
Learn survey design using common design structures followed by visualizing and analyzing survey results.
Probability & Statistics
Course
Network Analysis in R
- IntermediateSkill Level
- 4.8+
- 302
Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.
Probability & Statistics
Course
Practicing Statistics Interview Questions in Python
- AdvancedSkill Level
- 4.8+
- 302
Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.
Probability & Statistics
Course
Designing Machine Learning Workflows in Python
- AdvancedSkill Level
- 4.8+
- 298
Learn to build pipelines that stand the test of time.
Machine Learning
Course
AI-Assisted Restaurant Planning
- BasicSkill Level
- 4.8+
- 296
Interact with a customized GPT and use your prompting skills to plan and open your restaurant.
Artificial Intelligence
Course
Marketing Analytics in Google Sheets
- IntermediateSkill Level
- 4.8+
- 295
Learn how to ensure clean data entry and build dynamic dashboards to display your marketing data.
Reporting
Course
Inference for Categorical Data in R
- AdvancedSkill Level
- 4.8+
- 294
In this course youll learn how to leverage statistical techniques for working with categorical data.
Probability & Statistics
Course
Preparing for Your Associate Cloud Engineer Journey
- IntermediateSkill Level
- 4.7+
- 293
This course helps your preparation for the Associate Cloud Engineer exam, learn about the Google Cloud domains in the exam and create a study plan.
Cloud
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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