Course
Hyperparameter Tuning in Python
- IntermediateSkill Level
- 4.8+
- 864 reviews
Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.
Machine Learning
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199 Courses
Course
Practicing Coding Interview Questions in Python
- AdvancedSkill Level
- 4.7+
- 78 reviews
Prepare for your next coding interviews in Python.
Software Development
Course
Feature Engineering for NLP in Python
- IntermediateSkill Level
- 4.8+
- 154 reviews
Learn techniques to extract useful information from text and process them into a format suitable for machine learning.
Machine Learning
Course
Quantitative Risk Management in Python
- AdvancedSkill Level
- 4.8+
- 238 reviews
Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.
Applied Finance
Course
Fraud Detection in Python
- IntermediateSkill Level
- 4.7+
- 200 reviews
Learn how to detect fraud using Python.
Machine Learning
Course
Statistical Thinking in Python (Part 1)
- IntermediateSkill Level
- 4.8+
- 115 reviews
Build the foundation you need to think statistically and to speak the language of your data.
Probability & Statistics
Course
Introduction to AWS Boto in Python
- IntermediateSkill Level
- 4.8+
- 226 reviews
Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.
Cloud
Course
Monitoring Machine Learning in Python
- AdvancedSkill Level
- 4.8+
- 396 reviews
This course covers everything you need to know to build a basic machine learning monitoring system in Python
Machine Learning
Course
Market Basket Analysis in Python
- IntermediateSkill Level
- 4.8+
- 284 reviews
Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.
Machine Learning
Course
Intermediate Regression with statsmodels in Python
- IntermediateSkill Level
- 4.8+
- 603 reviews
Learn to perform linear and logistic regression with multiple explanatory variables.
Probability & Statistics
Course
Working with Geospatial Data in Python
- IntermediateSkill Level
- 4.8+
- 291 reviews
This course will show you how to integrate spatial data into your Python Data Science workflow.
Data Manipulation
Course
Sentiment Analysis in Python
- IntermediateSkill Level
- 4.8+
- 457 reviews
Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.
Machine Learning
Course
Introduction to Financial Concepts in Python
- BasicSkill Level
- 4.8+
- 452 reviews
Using Python and NumPy, learn the most fundamental financial concepts.
Applied Finance
Course
Databricks with the Python SDK
- AdvancedSkill Level
- 4.7+
- 94 reviews
Master Databricks with Python: learn to authenticate, manage clusters, automate jobs, and query AI models programmatically.
Artificial Intelligence
Course
Introduction to TensorFlow in Python
- IntermediateSkill Level
- 4.8+
- 56 reviews
Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.
Machine Learning
Course
ARIMA Models in Python
- AdvancedSkill Level
- 4.8+
- 423 reviews
Learn about ARIMA models in Python and become an expert in time series analysis.
Machine Learning
Course
Introduction to Network Analysis in Python
- IntermediateSkill Level
- 4.7+
- 226 reviews
This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.
Probability & Statistics
Course
Winning a Kaggle Competition in Python
- AdvancedSkill Level
- 4.8+
- 480 reviews
Learn how to approach and win competitions on Kaggle.
Machine Learning
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Introduction to MongoDB in Python
- IntermediateSkill Level
- 4.7+
- 388 reviews
Learn to manipulate and analyze flexibly structured data with MongoDB.
Data Engineering
Course
Biomedical Image Analysis in Python
- IntermediateSkill Level
- 4.8+
- 240 reviews
Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.
Data Manipulation
Course
Bayesian Data Analysis in Python
- IntermediateSkill Level
- 4.7+
- 266 reviews
Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!
Probability & Statistics
Course
Deep Reinforcement Learning in Python
- AdvancedSkill Level
- 4.8+
- 284 reviews
Learn and use powerful Deep Reinforcement Learning algorithms, including refinement and optimization techniques.
Artificial Intelligence
Course
Case Study: Building Software in Python
- AdvancedSkill Level
- 4.7+
- 307 reviews
Build real-world applications with Python—practice using OOP and software engineering principles to write clean and maintainable code.
Software Development
Course
Introduction to Python in Power BI
- IntermediateSkill Level
- 4.8+
- 151 reviews
Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.
Data Manipulation
Course
Introduction to Optimization in Python
- IntermediateSkill Level
- 4.7+
- 206 reviews
Learn to solve real-world optimization problems using Pythons SciPy and PuLP, covering everything from basic to constrained and complex optimization.
Software Development
Course
Machine Learning for Finance in Python
- IntermediateSkill Level
- 4.8+
- 220 reviews
Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.
Machine Learning
Course
Supply Chain Analytics in Python
- IntermediateSkill Level
- 4.8+
- 97 reviews
Leverage the power of Python and PuLP to optimize supply chains.
Exploratory Data Analysis
Course
Monte Carlo Simulations in Python
- IntermediateSkill Level
- 4.7+
- 171 reviews
Learn to design and run your own Monte Carlo simulations using Python!
Probability & Statistics
Course
Improving Your Data Visualizations in Python
- IntermediateSkill Level
- 4.7+
- 317 reviews
Learn to construct compelling and attractive visualizations that help communicate results efficiently and effectively.
Data Visualization
Course
Introduction to Predictive Analytics in Python
- BasicSkill Level
- 4.8+
- 239 reviews
In this course youll learn to use and present logistic regression models for making predictions.
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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