What jobs use Machine Learning Python?

Data Scientist : They use machine learning to analyze large amounts of raw data and convert them into actionable insights. Machine Learning Engineer : They design and build machine learning systems, conduct software tests, and implement machine learning algorithms. AI Engineer : They work on complex AI models using machine learning and deep learning. Data Analyst : They use machine learning to interpret complex data and help businesses make decisions. Research Scientist : They apply machine learning in scientific research to analyze and interpret complex data. Business Intelligence Developer : They use machine learning to analyze complex business data and provide insights. Big Data Engineer/Architect : They work with large amounts of data and use machine learning to analyze and interpret it. Quantitative Analyst : They use machine learning in financial institutions to identify profitable investment opportunities and risks. Computer Vision Engineer : They use machine learning to develop systems that can "understand" images and videos. NLP Scientist : They use machine learning to create systems that can understand human language. Robotics Engineer : They use machine learning to design and build intelligent and autonomous robots. Bioinformatics Scientist : They use machine learning to analyze and interpret complex biological data.

How to get started Machine Learning Python?

To get started with Machine Learning using Python on Coursera: Python Fundamentals : If new to Python, start with basic Python programming courses. ML Basics : Enroll in introductory machine learning courses, ensuring they're Python-centric. Dive into Libraries : Explore courses that cover Python ML libraries like scikit-learn, TensorFlow, and Keras. Hands-on Projects : Opt for courses with practical exercises where you can apply machine learning concepts using Python. Certify Your Skills : Finish courses and earn certificates to validate your expertise in machine learning with Python.

Top Machine Learning Python Courses - Learn Machine Learning Python Online

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Machine Learning Python

Results for "machine learning python"

Status: Free Trial
IBM
Python for Data Science, AI & Development
Skills you'll gain: Data Import/Export, Programming Principles, Web Scraping, Python Programming, Jupyter, Data Structures, Data Processing, Pandas (Python Package), Data Manipulation, JSON, Computer Programming, Restful API, NumPy, Object Oriented Programming (OOP), Scripting, Application Programming Interface (API), Automation, Data Analysis
4.6
Rating, 4.6 out of 5 stars
43K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
IBM
Machine Learning with Python
Skills you'll gain: Unsupervised Learning, Supervised Learning, Feature Engineering, Applied Machine Learning, Scikit Learn (Machine Learning Library), Machine Learning, Predictive Modeling, Dimensionality Reduction, Regression Analysis, Decision Tree Learning, Classification And Regression Tree (CART), Statistical Modeling
4.7
Rating, 4.7 out of 5 stars
18K reviews
Intermediate · Course · 1 - 3 Months
Status: New
Status: Free Trial
EDUCBA
AI Machine Learning with R & Python Projects
Skills you'll gain: Sampling (Statistics), Matplotlib, Data Analysis, Data Mining, Statistical Analysis, Statistical Hypothesis Testing, NumPy, Pandas (Python Package), Probability Distribution, Dimensionality Reduction, R Programming, Probability, Python Programming, Scikit Learn (Machine Learning Library), Linear Algebra, Applied Machine Learning, Unsupervised Learning, Regression Analysis, Statistical Methods, Artificial Intelligence and Machine Learning (AI/ML)
Beginner · Specialization · 3 - 6 Months
Status: New
Pearson
Skill Up with Python: Data Science and Machine Learning Recipes
Skills you'll gain: Pandas (Python Package), Web Scraping, Python Programming, Jupyter, Image Analysis, Text Mining, Data Manipulation, Computer Vision, Data Analysis, Natural Language Processing, Data Visualization Software, Data Science, Applied Machine Learning, Unstructured Data
Intermediate · Course · 1 - 4 Weeks
Status: Free Trial
Multiple educators
Machine Learning
Skills you'll gain: Unsupervised Learning, Supervised Learning, Classification And Regression Tree (CART), Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Tensorflow, Responsible AI, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Python Programming
4.9
Rating, 4.9 out of 5 stars
37K reviews
Beginner · Specialization · 1 - 3 Months
Status: Free Trial
EDHEC Business School
Investment Management with Python and Machine Learning
Skills you'll gain: Investment Management, Portfolio Management, Text Mining, Applied Machine Learning, Asset Management, Network Analysis, Data Visualization Software, Financial Data, Market Data, Unstructured Data, Web Scraping, Machine Learning, Social Network Analysis, Advanced Analytics, Financial Market, Financial Analysis, Financial Modeling, Return On Investment, Risk Analysis, Risk Management
4.6
Rating, 4.6 out of 5 stars
1.8K reviews
Beginner · Specialization · 3 - 6 Months

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Status: Free Trial
DeepLearning.AI
Supervised Machine Learning: Regression and Classification
Skills you'll gain: Supervised Learning, Applied Machine Learning, Jupyter, Scikit Learn (Machine Learning Library), Machine Learning, NumPy, Predictive Modeling, Feature Engineering, Artificial Intelligence, Classification And Regression Tree (CART), Python Programming, Regression Analysis, Statistical Modeling, Data Transformation
4.9
Rating, 4.9 out of 5 stars
31K reviews
Beginner · Course · 1 - 4 Weeks
Status: Free Trial
University of Michigan
Applied Machine Learning in Python
Skills you'll gain: Feature Engineering, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Decision Tree Learning, Unsupervised Learning, Python Programming, Dimensionality Reduction, Random Forest Algorithm, Regression Analysis
4.6
Rating, 4.6 out of 5 stars
8.6K reviews
Intermediate · Course · 1 - 4 Weeks
Status: Free Trial
IBM
Data Analysis with Python
Skills you'll gain: Exploratory Data Analysis, Data Wrangling, Data Transformation, Data Analysis, Data Cleansing, Data Manipulation, Data Import/Export, Predictive Modeling, Regression Analysis, Statistical Analysis, Pandas (Python Package), Scikit Learn (Machine Learning Library), Data-Driven Decision-Making, Matplotlib, Feature Engineering, Data Visualization, Data Pipelines, NumPy, Python Programming
4.7
Rating, 4.7 out of 5 stars
19K reviews
Intermediate · Course · 1 - 3 Months
Status: Free Trial
Status: AI skills
University of Pennsylvania
AI and Machine Learning Essentials with Python
Skills you'll gain: Statistical Machine Learning, PyTorch (Machine Learning Library), Statistical Methods, Probability, Probability & Statistics, Sampling (Statistics), Deep Learning, Probability Distribution, Python Programming, Supervised Learning, Statistics, Machine Learning Methods, Machine Learning, Regression Analysis, Data Processing, Agentic systems, Data Science, Artificial Intelligence, Artificial Neural Networks, Algorithms
4.5
Rating, 4.5 out of 5 stars
38 reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free Trial
Imperial College London
Mathematics for Machine Learning
Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Probability & Statistics, Machine Learning Algorithms, Jupyter, Data Science, Advanced Mathematics, Statistics, Statistical Analysis, Artificial Neural Networks, Algorithms, Data Manipulation, Python Programming, Machine Learning, Derivatives
4.6
Rating, 4.6 out of 5 stars
15K reviews
Beginner · Specialization · 3 - 6 Months
Status: New
Status: Free Trial
EDUCBA
Deep Learning with Python: CNN, ANN & RNN
Skills you'll gain: Keras (Neural Network Library), Image Analysis, Deep Learning, Artificial Neural Networks, Tensorflow, Data Processing, Computer Vision, Data Transformation, Financial Forecasting, Applied Machine Learning, Feature Engineering, Artificial Intelligence and Machine Learning (AI/ML), Data Visualization, Time Series Analysis and Forecasting, Exploratory Data Analysis, Python Programming, Customer Analysis, Predictive Modeling, Google Cloud Platform, Development Environment
Beginner · Specialization · 1 - 3 Months

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In summary, here are 10 of our most popular machine learning python courses

Python for Data Science, AI & Development: IBM
Machine Learning with Python: IBM
AI Machine Learning with R & Python Projects: EDUCBA
Skill Up with Python: Data Science and Machine Learning Recipes: Pearson
Machine Learning: DeepLearning.AI
Investment Management with Python and Machine Learning: EDHEC Business School
Supervised Machine Learning: Regression and Classification : DeepLearning.AI
Applied Machine Learning in Python: University of Michigan
Data Analysis with Python: IBM
AI and Machine Learning Essentials with Python: University of Pennsylvania

Skills you can learn in Data Analysis

Analytics (85)

Big Data (64)

Python Programming (47)

Business Analytics (40)

R Programming (37)

Statistical Analysis (36)

Sql (33)

Data Model (29)

Data Mining (27)

Exploratory Data Analysis (26)

Data Modeling (21)

Data Manipulation (20)

Frequently Asked Questions about Machine Learning Python

Machine Learning Python refers to the use of the Python programming language in the field of machine learning. Python is a popular choice due to its simplicity and large community. It offers various libraries and frameworks like Scikit-Learn, TensorFlow, PyTorch, and Keras that make it easier to develop machine-learning models. Building machine-learning Python skills involves learning Python programming, understanding machine-learning algorithms, and gaining proficiency in using these libraries and frameworks. This can be achieved through various online courses, tutorials, and hands-on projects.‎

Data Scientist: They use machine learning to analyze large amounts of raw data and convert them into actionable insights.
Machine Learning Engineer: They design and build machine learning systems, conduct software tests, and implement machine learning algorithms.
AI Engineer: They work on complex AI models using machine learning and deep learning.
Data Analyst: They use machine learning to interpret complex data and help businesses make decisions.
Research Scientist: They apply machine learning in scientific research to analyze and interpret complex data.
Business Intelligence Developer: They use machine learning to analyze complex business data and provide insights.
Big Data Engineer/Architect: They work with large amounts of data and use machine learning to analyze and interpret it.
Quantitative Analyst: They use machine learning in financial institutions to identify profitable investment opportunities and risks.
Computer Vision Engineer: They use machine learning to develop systems that can "understand" images and videos.
NLP Scientist: They use machine learning to create systems that can understand human language.
Robotics Engineer: They use machine learning to design and build intelligent and autonomous robots.
Bioinformatics Scientist: They use machine learning to analyze and interpret complex biological data.‎

To get started with Machine Learning using Python on Coursera:

Python Fundamentals: If new to Python, start with basic Python programming courses.
ML Basics: Enroll in introductory machine learning courses, ensuring they're Python-centric.
Dive into Libraries: Explore courses that cover Python ML libraries like scikit-learn, TensorFlow, and Keras.
Hands-on Projects: Opt for courses with practical exercises where you can apply machine learning concepts using Python.
Certify Your Skills: Finish courses and earn certificates to validate your expertise in machine learning with Python. ‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.