Course
HR Analytics: Exploring Employee Data in R
- IntermediateSkill Level
- 4.8+
- 343
Learn how to manipulate, visualize, and perform statistical tests through a series of HR analytics case studies.
Exploratory Data Analysis
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Course
Gemini in Google Drive
- BasicSkill Level
- 4.9+
- 341
Organize and manage files with Gemini in Google Drive. Use AI-powered search to quickly find information, streamline collaboration, and boost productivity.
Artificial Intelligence
Course
AI-Assisted Product Launch
- BasicSkill Level
- 4.8+
- 341
Analyze market dynamics and craft a strategic entry plan for an EV manufacturer using generative AI.
Artificial Intelligence
Course
Introduction to Data Versioning with DVC
- IntermediateSkill Level
- 4.8+
- 340
Explore Data Version Control for ML data management. Master setup, automate pipelines, and evaluate models seamlessly.
Machine Learning
Course
Case Study: Inventory Analysis in Power BI
- IntermediateSkill Level
- 4.8+
- 340
This Power BI case study follows a real-world business use case on tackling inventory analysis using DAX and visualizations.
Data Visualization
Course
Data Fluency
- BasicSkill Level
- 4.8+
- 338
Master data fluency! Learn skills for individuals and organizations, understand behaviors, and build a data-fluent culture.
Data Literacy
Course
Interactive Maps with leaflet in R
- BasicSkill Level
- 4.7+
- 338
Learn how to produce interactive web maps with ease using leaflet.
Data Visualization
Course
Analyzing Financial Statements in Python
- IntermediateSkill Level
- 4.7+
- 338
Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.
Applied Finance
Course
Create Engaging Video with Google Vids
- BasicSkill Level
- 4.9+
- 336
Create and refine videos faster with Gemini in Google Vids. Use AI-powered storyboarding and content generation to produce polished videos with ease.
Cloud
Course
GARCH Models in Python
- IntermediateSkill Level
- 4.8+
- 336
Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.
Applied Finance
Course
Advanced Deep Learning with Keras
- IntermediateSkill Level
- 4.8+
- 334
Learn how to develop deep learning models with Keras.
Artificial Intelligence
Course
AI-Assisted Restaurant Planning
- BasicSkill Level
- 4.8+
- 334
Interact with a customized GPT and use your prompting skills to plan and open your restaurant.
Artificial Intelligence
Course
Case Study: Analyzing City Time Series Data in R
- IntermediateSkill Level
- 4.9+
- 333
Strengthen your knowledge of the topics covered in Manipulating Time Series in R using real case study data.
Probability & Statistics
Course
Spoken Language Processing in Python
- AdvancedSkill Level
- 4.8+
- 332
Learn how to load, transform, and transcribe speech from raw audio files in Python.
Data Manipulation
Course
Designing Machine Learning Workflows in Python
- AdvancedSkill Level
- 4.8+
- 330
Learn to build pipelines that stand the test of time.
Machine Learning
Course
Fundamentals of Bayesian Data Analysis in R
- IntermediateSkill Level
- 4.9+
- 329
Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.
Probability & Statistics
Course
Multi-Modal Models with Hugging Face
- IntermediateSkill Level
- 4.8+
- 329
Combine text, images, audio, and video with the latest AI models from Hugging Face, and generate new images and videos!
Artificial Intelligence
Course
Categorical Data in the Tidyverse
- BasicSkill Level
- 4.8+
- 328
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
Gemini in Google Meet
- BasicSkill Level
- 4.9+
- 326
Enhance virtual meetings with Gemini in Google Meet. Leverage AI-driven summaries, notes, and tools to make every meeting more efficient and actionable.
Artificial Intelligence
Course
Object-Oriented Programming with S3 and R6 in R
- AdvancedSkill Level
- 4.8+
- 323
Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.
Software Development
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
Recurrent Neural Networks (RNNs) for Language Modeling with Keras
- AdvancedSkill Level
- 4.8+
- 319
Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.
Artificial Intelligence
Course
Azure Compute Solutions
- IntermediateSkill Level
- 4.8+
- 316
Learn how containers work in Azure, including registries, ACI, AKS basics, scaling, monitoring, and troubleshooting.
Cloud
Course
Building Agentic Workflows with LlamaIndex
- AdvancedSkill Level
- 4.7+
- 315
Build AI agentic workflows that can plan, search, remember, and collaborate, using LlamaIndex.
Artificial Intelligence
Course
Hierarchical and Recursive Queries in SQL Server
- AdvancedSkill Level
- 4.8+
- 312
Learn how to write recursive queries and query hierarchical data structures.
Software Development
Course
Customer Segmentation in Python
- IntermediateSkill Level
- 4.9+
- 311
Learn how to segment customers in Python.
Data Manipulation
Course
Inference for Numerical Data in R
- AdvancedSkill Level
- 4.9+
- 307
In this course youll learn techniques for performing statistical inference on numerical data.
Probability & Statistics
Course
Building Chatbots in Python
- IntermediateSkill Level
- 4.7+
- 306
Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.
Machine Learning
Course
Querying a PostgreSQL Database in Java
- AdvancedSkill Level
- 4.8+
- 304
Connect Java to PostgreSQL with JDBC. Write secure queries, manage transactions, and handle large datasets efficiently.
Software Development
Course
Introduction to Portfolio Analysis in R
- BasicSkill Level
- 4.8+
- 303
Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.
Applied Finance
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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