Course
Data Structures and Algorithms in Python
- AdvancedSkill Level
- 4.8+
- 3.3K
Explore data structures such as linked lists, stacks, queues, hash tables, and graphs; and search and sort algorithms!
Software Development
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Course
Introduction to Apache Airflow in Python
- AdvancedSkill Level
- 4.8+
- 2.7K
Learn how to implement and schedule data engineering workflows.
Data Engineering
Course
Big Data Fundamentals with PySpark
- AdvancedSkill Level
- 4.7+
- 2K
Learn the fundamentals of working with big data with PySpark.
Data Engineering
Course
Object-Oriented Programming in Python
- AdvancedSkill Level
- 4.8+
- 2K
Dive in and learn how to create classes and leverage inheritance and polymorphism to reuse and optimize code.
Software Development
Course
Deep Learning for Images with PyTorch
- AdvancedSkill Level
- 4.8+
- 1.8K
Apply PyTorch to images and use deep learning models for object detection with bounding boxes and image segmentation generation.
Artificial Intelligence
Course
Advanced Git
- AdvancedSkill Level
- 4.8+
- 1.6K
Master Git’s advanced features to streamline data science and engineering workflows, from complex merging to large-scale project optimization.
Software Development
Course
Multi-Agent Systems with LangGraph
- AdvancedSkill Level
- 4.9+
- 1.6K
Build powerful multi-agent systems by applying emerging agentic design patterns in the LangGraph framework.
Artificial Intelligence
Course
Transformer Models with PyTorch
- AdvancedSkill Level
- 4.8+
- 1.4K
What makes LLMs tick? Discover how transformers revolutionized text modeling and kickstarted the generative AI boom.
Artificial Intelligence
Course
Introduction to Testing in Python
- AdvancedSkill Level
- 4.8+
- 1.4K
Master Python testing: Learn methods, create checks, and ensure error-free code with pytest and unittest.
Software Development
Course
Intermediate dbt
- AdvancedSkill Level
- 4.8+
- 1.3K
Take your dbt skills to the next level with this hands-on course designed for data engineers and analytics professionals.
Data Engineering
Course
Introduction to MLflow
- AdvancedSkill Level
- 4.8+
- 1.2K
Learn how to use MLflow to simplify the complexities of building machine learning applications. Explore MLflow tracking, projects, models, and model registry.
Machine Learning
Course
Deep Learning for Text with PyTorch
- AdvancedSkill Level
- 4.8+
- 1.2K
Discover the exciting world of Deep Learning for Text with PyTorch and unlock new possibilities in natural language processing and text generation.
Artificial Intelligence
Course
Reinforcement Learning with Gymnasium in Python
- AdvancedSkill Level
- 4.8+
- 1.1K
Start your reinforcement learning journey! Learn how agents can learn to solve environments through interactions.
Artificial Intelligence
Course
Machine Learning with PySpark
- AdvancedSkill Level
- 4.8+
- 933
Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.
Machine Learning
Course
Machine Learning for Time Series Data in Python
- AdvancedSkill Level
- 4.8+
- 895
This course focuses on feature engineering and machine learning for time series data.
Machine Learning
Course
Cleaning Data with PySpark
- AdvancedSkill Level
- 4.8+
- 873
Learn how to clean data with Apache Spark in Python.
Data Preparation
Course
Deploying AI into Production with FastAPI
- AdvancedSkill Level
- 4.8+
- 869
Learn how to use FastAPI to develop APIs that support AI models, built to meet real-world demands.
Artificial Intelligence
Course
MLOps Deployment and Life Cycling
- AdvancedSkill Level
- 4.8+
- 862
In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.
Machine Learning
Course
Intermediate Object-Oriented Programming in Python
- AdvancedSkill Level
- 4.8+
- 835
Build your OOP skills with descriptors, multilevel inheritance, and abstract base classes!
Software Development
Course
Image Modeling with Keras
- AdvancedSkill Level
- 4.9+
- 820
Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.
Artificial Intelligence
Course
Calculations in Tableau
- AdvancedSkill Level
- 4.8+
- 791
In this interactive course, you’ll learn how to use functions for your Tableau calculations and when you should use them!
Data Visualization
Course
CI/CD for Machine Learning
- AdvancedSkill Level
- 4.8+
- 698
Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control
Machine Learning
Course
Case Study: Building E-Commerce Data Models with dbt
- AdvancedSkill Level
- 4.8+
- 682
Learn how to transform raw data into clean, reliable models with dbt through hands-on, real-world exercises.
Data Engineering
Course
Feature Engineering for NLP in Python
- AdvancedSkill Level
- 4.9+
- 615
Learn techniques to extract useful information from text and process them into a format suitable for machine learning.
Machine Learning
Course
AI Agents with Hugging Face smolagents
- AdvancedSkill Level
- 4.8+
- 572
Learn how to build intelligent agents that reason, act, and solve real-world tasks using Python.
Artificial Intelligence
Course
Quantitative Risk Management in Python
- AdvancedSkill Level
- 4.8+
- 541
Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.
Applied Finance
Course
Practicing Coding Interview Questions in Python
- AdvancedSkill Level
- 4.8+
- 536
Prepare for your next coding interviews in Python.
Software Development
Course
Deep Reinforcement Learning in Python
- AdvancedSkill Level
- 4.8+
- 496
Learn and use powerful Deep Reinforcement Learning algorithms, including refinement and optimization techniques.
Artificial Intelligence
Course
Ensemble Methods in Python
- AdvancedSkill Level
- 4.9+
- 481
Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.
Machine Learning
Course
ARIMA Models in Python
- AdvancedSkill Level
- 4.9+
- 466
Learn about ARIMA models in Python and become an expert in time series analysis.
Machine Learning
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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