Course
Introduction to GCP
- BasicSkill Level
- 4.8+
- 413
Get to know the Google Cloud Platform (GCP) with this course on storage, data handling, and business modernization using GCP.
Cloud
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Course
Foundations of Probability in Python
- IntermediateSkill Level
- 4.8+
- 412
Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.
Probability & Statistics
Course
Introduction to Portfolio Analysis in Python
- AdvancedSkill Level
- 4.9+
- 409
Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.
Applied Finance
Course
Fraud Detection in Python
- IntermediateSkill Level
- 4.8+
- 408
Learn how to detect fraud using Python.
Machine Learning
Course
Dealing with Missing Data in Python
- IntermediateSkill Level
- 4.8+
- 405
Learn how to identify, analyze, remove and impute missing data in Python.
Data Manipulation
Course
ARIMA Models in Python
- AdvancedSkill Level
- 4.9+
- 404
Learn about ARIMA models in Python and become an expert in time series analysis.
Machine Learning
Course
Visualizing Time Series Data in Python
- IntermediateSkill Level
- 4.8+
- 404
Visualize seasonality, trends and other patterns in your time series data.
Data Visualization
Course
Cluster Analysis in R
- IntermediateSkill Level
- 4.9+
- 402
Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.
Machine Learning
Course
Case Study: Analyzing Job Market Data in Tableau
- BasicSkill Level
- 4.8+
- 402
In this case study, you’ll use visualization techniques to find out what skills are most in-demand for data scientists, data analysts, and data engineers.
Data Visualization
Course
Streaming Concepts
- BasicSkill Level
- 4.8+
- 401
Learn about the difference between batching and streaming, scaling streaming systems, and real-world applications.
Data Engineering
Course
Intermediate Data Visualization with Seaborn
- IntermediateSkill Level
- 4.9+
- 399
Use Seaborns sophisticated visualization tools to make beautiful, informative visualizations with ease.
Data Visualization
Course
Understanding Digital Transformation
- BasicSkill Level
- 4.8+
- 399
Dive into the world of digital transformation and equip yourself to be an agent of change in a rapidly evolving digital landscape.
Data Literacy
Course
Corporate Finance Fundamentals
- BasicSkill Level
- 4.8+
- 399
Learn key financial concepts such as capital investment, WACC, and shareholder value.
Applied Finance
Course
Window Functions in Snowflake
- IntermediateSkill Level
- 4.9+
- 396
Discover Snowflake window functions to solve complex data problems with rankings, partitions, and rolling calculations.
Data Manipulation
Course
Introduction to AWS Boto in Python
- IntermediateSkill Level
- 4.8+
- 395
Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.
Cloud
Course
Transform and Analyze Data with Microsoft Fabric
- BasicSkill Level
- 4.8+
- 395
Learn how to transform and analyze data within your Microsoft Fabric account
Other
Course
Digital Transformation with Google Cloud
- BasicSkill Level
- 4.9+
- 393
This course provides an overview of the opportunities and challenges companies encounter in their digital transformation journey.
Cloud
Course
Gen AI Agents: Transform Your Organization
- BasicSkill Level
- 4.9+
- 393
This course explores how organizations can use custom gen AI agents to help tackle specific business challenges.
Cloud
Course
Data Modeling in Sigma
- BasicSkill Level
- 4.9+
- 383
Stop rewriting the same joins and calculations, and dive into well-governed, scalable analytics using Sigma data models.
Reporting
Course
Introduction to AI Apps in Sigma
- BasicSkill Level
- 4.9+
- 382
Build interactive AI apps in Sigma using user input, actions, and polished interfaces, no coding required.
Reporting
Course
AI for Sales
- BasicSkill Level
- 4.7+
- 381
Tackle your sales work in an AI-first way! Learn to automate prospecting, draft personalized emails, and streamline CRM tasks using AI.
Artificial Intelligence
Course
Graph RAG with LangChain and Neo4j
- AdvancedSkill Level
- 4.8+
- 379
Create more accurate and reliable RAG systems with Graph RAG and hybrid RAG.
Artificial Intelligence
Course
Data Processing in Shell
- IntermediateSkill Level
- 4.8+
- 378
Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.
Data Manipulation
Course
AI-Assisted Travel Planning
- BasicSkill Level
- 4.8+
- 378
Master travel planning with WanderBot: craft prompts, build confidence, and streamline your next adventure.
Artificial Intelligence
Course
Spoken Language Processing in Python
- AdvancedSkill Level
- 4.8+
- 374
Learn how to load, transform, and transcribe speech from raw audio files in Python.
Data Manipulation
Course
Improving Query Performance in PostgreSQL
- IntermediateSkill Level
- 4.8+
- 374
Learn how to structure your PostgreSQL queries to run in a fraction of the time.
Software Development
Course
Monitoring Machine Learning Concepts
- IntermediateSkill Level
- 4.8+
- 371
Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.
Machine Learning
Course
Visualizing Geospatial Data in Python
- IntermediateSkill Level
- 4.8+
- 370
Learn how to make attractive visualizations of geospatial data in Python using the geopandas package and folium maps.
Data Visualization
Course
Multi-Modal Systems with the OpenAI API
- IntermediateSkill Level
- 4.9+
- 366
Create multi-modal systems using OpenAIs text and audio models, including an end-to-end customer support chatbot!
Artificial Intelligence
Course
Reinforcement Learning from Human Feedback (RLHF)
- AdvancedSkill Level
- 4.8+
- 366
Learn how to make GenAI models truly reflect human values while gaining hands-on experience with advanced LLMs.
Artificial Intelligence
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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