This specialization will prepare learners to enter the exciting fields of artificial intelligence (AI) and machine learning. Across four courses, learners will familiarize themselves with AI, machine learning and deep learning essentials, while also gaining experience with statistics–the backbone of any machine learning problem. Learners will use Python to write programs that accomplish basic AI and machine learning tasks. By the end of this specialization, learners will be able to confidently use and discuss AI and machine learning tools and concepts, improve their Python skills, and be primed for more advanced study in these fields.
AI and Machine Learning Essentials with Python Specialization
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AI and Machine Learning Essentials with Python Specialization
Explore AI and Machine Learning. Go further with your Python skills while exploring the transformative fields of artificial intelligence, machine learning and deep learning.
Instructors: Victor Preciado
2,702 already enrolled
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Get in-depth knowledge of a subject
4.6
(28 reviews)
Intermediate level
Recommended experience
4 months at 8 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
4.6
(28 reviews)
Intermediate level
Recommended experience
4 months at 8 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
Understand the philosophical, scientific, and historical foundations of artificial intelligence and machine learning.
Apply Python programming concepts to implement AI algorithms, machine learning models, and deep learning architectures.
Use essential statistics concepts, like probability, linear algebra and statistical learning theory, to develop and analyze machine learning models.
Implement and compare machine learning algorithms, such as linear regression and logistic regression, for both regression and classification tasks.
Overview
Skills you'll gain
- Artificial Neural Networks
- Agentic systems
- Statistics
- Probability
- Regression Analysis
- Statistical Machine Learning
- Deep Learning
- Machine Learning Methods
- Machine Learning
- Probability Distribution
- Algorithms
- Supervised Learning
- Statistical Analysis
- Data Processing
- Probability & Statistics
- Data Science
- Artificial Intelligence
- Sampling (Statistics)
Tools you'll learn
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
52 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from University of Pennsylvania
Specialization - 4 course series
What you'll learn
Understand the history and context of artificial intelligence through the lenses of philosophy and science fiction.
Explore different kinds of common search algorithms like A* Search, depth first search, breadth first search and more.
Skills you'll gain
Category: Artificial Intelligence
Category: Algorithms
Category: Python Programming
Category: Computer Science
Category: Agentic systems
Category: Computer Programming
Category: Theoretical Computer Science
What you'll learn
Comprehensively review probability and understand its role as a building block of data science.
Apply the central limit theorem, confidence intervals and the method of maximum likelihood to solving data science problems.
Skills you'll gain
Category: Probability & Statistics
Category: Probability
Category: Statistical Inference
Category: Statistics
Category: Sampling (Statistics)
Category: Data Science
Category: Probability Distribution
Category: General Mathematics
Category: Descriptive Statistics
Category: Statistical Analysis
What you'll learn
Review probability basics and understand essential theoretical framework to analyze statistical learning problems.
Use linear regression and Python programming to solve machine learning problems.
Skills you'll gain
Category: Regression Analysis
Category: Statistical Inference
Category: Probability & Statistics
Category: Statistical Machine Learning
Category: Python Programming
Category: Machine Learning
Category: Statistical Analysis
Category: Predictive Modeling
Category: Applied Machine Learning
Category: Machine Learning Methods
Category: Classification And Regression Tree (CART)
Category: Supervised Learning
What you'll learn
Understand the history and context of the deep learning field, and explore what "intelligence" really means.
Explore deep learning models like the perceptron, neural networks and backpropagation, and study the techniques that drive them.
Code a project using Python where you will preprocess data and use your data to train a Support Vector Machine (SVM.)
Skills you'll gain
Category: Deep Learning
Category: Artificial Neural Networks
Category: Machine Learning Algorithms
Category: Machine Learning
Category: PyTorch (Machine Learning Library)
Category: Data Processing
Category: Computer Vision
Category: Artificial Intelligence
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Instructors
2 Courses1,104 learners
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Frequently asked questions
Learners should have Python programming skills. We recommend completing the Introduction to Programming with Python and Java Specialization or having similar knowledge. Basic Python will be reviewed in the first course of the specialization.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
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Financial aid available,