Learn Python for AI and machine learning with practical projects and industry-relevant skills.
Basic algebra and statistics helpful but not required
Any programming experience; Python preferred
Data Analysis with Python
BeginnerApplied Text Mining in Python
BeginnerCleaning Data in Python
BeginnerDealing with Missing Data in Python
AdvancedExploratory Data Analysis in Python
IntermediateHypothesis Testing with Python
IntermediateLinear Classifiers in Python
IntermediateMachine Learning with Scikit-learn
BeginnerMachine Learning with Python: from Linear Models to Deep Learning
BeginnerComputer Vision and Image Processing with Python
BeginnerMachine Learning with Python: A Practical Introduction
BeginnerLinear Regression in Python
BeginnerData Wrangling with Pandas
BeginnerData Analysis with Python
BeginnerApplied Text Mining in Python
BeginnerCleaning Data in Python
BeginnerDealing with Missing Data in Python
AdvancedExploratory Data Analysis in Python
IntermediateHypothesis Testing with Python
IntermediateLinear Classifiers in Python
IntermediateMachine Learning with Scikit-learn
BeginnerMachine Learning with Python: from Linear Models to Deep Learning
BeginnerComputer Vision and Image Processing with Python
BeginnerMachine Learning with Python: A Practical Introduction
BeginnerLinear Regression in Python
BeginnerData Wrangling with Pandas
BeginnerFollow these courses in order to complete the learning path. Click on any course to enroll.
Part of the IBM Data Analyst Professional Certificate, this course covers the fundamentals of data analysis using Python, including working with data, exploratory data analysis, and an introduction to machine learning models.
Part of the Applied Data Science with Python Specialization, this course provides an introduction to text mining and NLP. It covers understanding and manipulating text data in Python, including topic modeling and text classification.
This course provides a comprehensive introduction to data cleaning with Python. You'll learn to diagnose your data's dirtiness, and develop the skills to clean it. You'll deal with common data problems like missing values, inconsistent data types, and duplicates.
This course focuses on various techniques to handle missing data in Python using libraries like pandas and Scikit-Learn, covering both simple and advanced imputation methods.
This course covers the process of exploring and analyzing data, from understanding a dataset to incorporating findings into a data science workflow. You will use Python to summarize, validate, and clean data.
This hands-on course from Data Camp teaches you how to conduct hypothesis tests in Python. You will learn about different types of tests, including t-tests and chi-squared tests, and how to interpret their results. The course is interactive and includes many coding exercises.
Learn to build, interpret, and tune linear classifiers, including logistic regression and support vector machines, using Scikit-Learn.
This course provides a comprehensive introduction to the Scikit-Learn library, the most popular Python library for machine learning. You'll learn how to use Scikit-Learn for a variety of machine learning tasks, including regression.
An in-depth introduction to machine learning, covering topics from linear models to deep learning. The syllabus includes on-line algorithms and support vector machines, with practical implementation in Python projects.
This course offers a beginner-friendly introduction to the core concepts of computer vision using Python. You will learn to manipulate images, detect features like faces and eyes, and perform object recognition with popular libraries like OpenCV and Dlib.
This course provides a practical introduction to machine learning using Python. It covers the entire machine learning workflow, from data preparation and feature engineering to model building and evaluation.
This free course teaches you the fundamentals of linear regression and its implementation in Python. It is a beginner-friendly course that covers the theory and practical aspects of this important machine learning algorithm.
This course provides a comprehensive introduction to data wrangling with the Pandas library in Python, covering essential data cleaning and transformation techniques.
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