Python for Machine Learning Courses
Python for machine learning courses can help you learn data manipulation, algorithm implementation, model evaluation, and feature selection. You can build skills in data visualization, hyperparameter tuning, and understanding neural networks. Many courses introduce tools like TensorFlow, Scikit-learn, and Pandas, that support applying your skills in real-world projects, enabling you to create predictive models and analyze complex datasets effectively.
Popular Python for Machine Learning Courses and Certifications
Skills you'll gain: Data Import/Export, Programming Principles, Web Scraping, File I/O, Python Programming, Jupyter, Data Structures, Pandas (Python Package), Data Manipulation, JSON, Computer Programming, Restful API, NumPy, Object Oriented Programming (OOP), Application Programming Interface (API), Automation, Data Analysis
Skills you'll gain: Unsupervised Learning, Supervised Learning, Model Evaluation, Regression Analysis, Scikit Learn (Machine Learning Library), Applied Machine Learning, Predictive Modeling, Machine Learning, Dimensionality Reduction, Decision Tree Learning, Python Programming, Logistic Regression, Classification Algorithms, Feature Engineering
Skills you'll gain: Seaborn, Data Storytelling, Data Integration, A/B Testing, Data Import/Export, Statistical Hypothesis Testing, Statistical Methods, Text Mining, Data-Driven Decision-Making, Git (Version Control System), Data Presentation, Matplotlib, Data Visualization, Pandas (Python Package), Version Control, GitHub, Statistical Analysis, Exploratory Data Analysis, Jupyter, NumPy
Skills you'll gain: Matplotlib, NumPy, Pandas (Python Package), Model Evaluation, Data Preprocessing, Regression Analysis, Scikit Learn (Machine Learning Library), Data Manipulation, Machine Learning, Feature Engineering, Exploratory Data Analysis, Applied Machine Learning, Supervised Learning, Python Programming
Skills you'll gain: Exploratory Data Analysis, Data Analysis, Data Import/Export, Data Manipulation, Data Transformation, Predictive Modeling, Data Cleansing, Data Preprocessing, Model Evaluation, Predictive Analytics, Pandas (Python Package), Regression Analysis, Feature Engineering, Statistical Analysis, Matplotlib, Scikit Learn (Machine Learning Library), Data Visualization, NumPy, Python Programming
Imperial College London
Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Data Preprocessing, Unsupervised Learning, Feature Engineering, Machine Learning Algorithms, Jupyter, Advanced Mathematics, Statistics, Artificial Neural Networks, Algorithms, Mathematical Modeling, Python Programming, Derivatives
What brings you to Coursera today?
University of Michigan
Skills you'll gain: Feature Engineering, Model Evaluation, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Decision Tree Learning, Unsupervised Learning, Python Programming, Random Forest Algorithm, Regression Analysis, Classification Algorithms, Artificial Neural Networks
Skills you'll gain: Object Oriented Programming (OOP), Unit Testing, Test Driven Development (TDD), Programming Principles, Software Testing, Data Structures, Python Programming, Computer Programming, Development Environment, Debugging, Integrated Development Environments, Django (Web Framework), Cloud Hosting
DeepLearning.AI
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Mathematical Modeling, Data Preprocessing, Machine Learning, Machine Learning Methods
Skills you'll gain: Supervised Learning, Feature Engineering, Applied Machine Learning, Object Oriented Programming (OOP), Unsupervised Learning, Model Evaluation, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Transfer Learning, Machine Learning Algorithms, Data Visualization, Natural Language Processing, Seaborn, Predictive Modeling, Flask (Web Framework), Python Programming, Deep Learning, PyTorch (Machine Learning Library), Programming Principles, Web Applications
Google
Skills you'll gain: Program Development, Programming Principles, Python Programming, Computer Programming, Computational Thinking, Problem Management, Data Structures, Integrated Development Environments, Debugging, Development Environment
Multiple educators
Skills you'll gain: Unsupervised Learning, Supervised Learning, Transfer Learning, Machine Learning, Jupyter, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Data Preprocessing
In summary, here are 10 of our most popular python for machine learning courses
- Python for Data Science, AI & Development: IBM
- Machine Learning with Python: IBM
- Python for Real-World Data Analysis: Coursera
- Learn & Build Machine Learning Models with Python: EDUCBA
- Data Analysis with Python: IBM
- Mathematics for Machine Learning: Imperial College London
- Applied Machine Learning in Python: University of Michigan
- Programming in Python: Meta
- Mathematics for Machine Learning and Data Science: DeepLearning.AI
- AI & Python Development Megaclass: Packt
