Course
Supply Chain Analytics in Python
- IntermediateSkill Level
- 4.8+
- 307
Leverage the power of Python and PuLP to optimize supply chains.
Exploratory Data Analysis
Data, AI, and Cloud Courses
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Course
Functions for Manipulating Data in SQL Server
- IntermediateSkill Level
- 4.9+
- 305
Learn the most important functions for manipulating, processing, and transforming data in SQL Server.
Data Manipulation
Course
Optimizing Code in Java
- AdvancedSkill Level
- 4.8+
- 304
Learn key techniques to optimize Java performance, from algorithm efficiency to JVM tuning and multithreading.
Software Development
Course
AI-Assisted Product Launch
- BasicSkill Level
- 4.8+
- 303
Analyze market dynamics and craft a strategic entry plan for an EV manufacturer using generative AI.
Artificial Intelligence
Course
Monitoring Machine Learning in Python
- AdvancedSkill Level
- 4.8+
- 302
This course covers everything you need to know to build a basic machine learning monitoring system in Python
Machine Learning
Course
Transactions and Error Handling in SQL Server
- IntermediateSkill Level
- 4.8+
- 301
Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.
Software Development
Course
Advanced Deep Learning with Keras
- IntermediateSkill Level
- 4.8+
- 301
Learn how to develop deep learning models with Keras.
Artificial Intelligence
Course
Object-Oriented Programming with S3 and R6 in R
- AdvancedSkill Level
- 4.8+
- 300
Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.
Software Development
Course
Analyzing Survey Data in R
- IntermediateSkill Level
- 4.8+
- 298
Learn survey design using common design structures followed by visualizing and analyzing survey results.
Probability & Statistics
Course
Introduction to DataLab
- BasicSkill Level
- 4.9+
- 297
Learn the fundamentals of using DataLab, an AI-powered data notebook for data analysis and exploration.
Reporting
Course
Databricks with the Python SDK
- AdvancedSkill Level
- 4.8+
- 297
Master Databricks with Python: learn to authenticate, manage clusters, automate jobs, and query AI models programmatically.
Artificial Intelligence
Course
Baseball Data Visualization in Power BI
- BasicSkill Level
- 4.9+
- 295
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
Exploring Data Transformation with Google Cloud
- BasicSkill Level
- 4.9+
- 294
Exploring Data Transformation with Google Cloud
Cloud
Course
Building AI Agents with CrewAI
- IntermediateSkill Level
- 4.8+
- 294
Build AI teams that work together, automate workflows, and generate content with CrewAI.
Artificial Intelligence
Course
Case Study: Inventory Analysis in Power BI
- IntermediateSkill Level
- 4.8+
- 294
This Power BI case study follows a real-world business use case on tackling inventory analysis using DAX and visualizations.
Data Visualization
Course
Plan and Implement a Data Analytics Environment with Microsoft Fabric
- BasicSkill Level
- 4.8+
- 291
Learn how to set up and manage your Microsoft Fabric infrastructure.
Other
Course
Network Analysis in R
- IntermediateSkill Level
- 4.8+
- 291
Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.
Probability & Statistics
Course
Generalized Linear Models in Python
- AdvancedSkill Level
- 4.8+
- 290
Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.
Probability & Statistics
Course
Gen AI Apps: Transform Your Work
- BasicSkill Level
- 4.8+
- 288
This course introduces Google’s gen AI applications, such as Google Workspace with Gemini and NotebookLM.
Cloud
Course
Financial Modeling in Google Sheets
- IntermediateSkill Level
- 4.8+
- 288
Learn basic business modeling including cash flows, investments, annuities, loan amortization, and more using Google Sheets.
Applied Finance
Course
Fine-Tuning with Llama 3
- IntermediateSkill Level
- 4.7+
- 287
Fine-tune Llama for custom tasks using TorchTune, and learn techniques for efficient fine-tuning such as quantization.
Artificial Intelligence
Course
Inference for Categorical Data in R
- AdvancedSkill Level
- 4.8+
- 286
In this course youll learn how to leverage statistical techniques for working with categorical data.
Probability & Statistics
Course
Practicing Statistics Interview Questions in Python
- AdvancedSkill Level
- 4.8+
- 285
Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.
Probability & Statistics
Course
Introduction to Python in Power BI
- IntermediateSkill Level
- 4.9+
- 283
Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.
Data Manipulation
Course
Introduction to Databricks Genie
- BasicSkill Level
- 4.8+
- 283
Ask data questions in plain English with Databricks Genie - build spaces, curate business language, and monitor quality.
Data Engineering
Course
Winning a Kaggle Competition in Python
- AdvancedSkill Level
- 4.8+
- 282
Learn how to approach and win competitions on Kaggle.
Machine Learning
Course
AI-Assisted Restaurant Planning
- BasicSkill Level
- 4.8+
- 282
Interact with a customized GPT and use your prompting skills to plan and open your restaurant.
Artificial Intelligence
Course
Inference for Numerical Data in R
- AdvancedSkill Level
- 4.9+
- 280
In this course youll learn techniques for performing statistical inference on numerical data.
Probability & Statistics
Course
Advanced AI-Assisted Coding for Developers
- AdvancedSkill Level
- 4.9+
- 279
Learn to use AI as a senior engineering partner for code analysis, performance optimization, security, and software architecture decisions.
Artificial Intelligence
Course
Decoding Decision Modeling
- BasicSkill Level
- 4.8+
- 279
Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.
Data Literacy
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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