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AI Programming with Python

Nanodegree Program

Learn Python, NumPy, pandas, Matplotlib, PyTorch, Calculus, and Linear Algebra—the foundations for building your own neural network.

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06Days08Hrs48Min57Sec

  • Estimated time
    3 Months

    At 10 hrs/week

  • Enroll by
    December 14, 2022

    Get access to classroom immediately on enrollment

  • Prerequisites
    Basic Algebra and Programming Knowledge

What you will learn

  1. Learn AI Fundamentals

    3 months to complete

    Learn the essential foundations of AI: the programming tools (Python, NumPy, PyTorch), the math (calculus and linear algebra), and the key techniques of neural networks (gradient descent and backpropagation).

    Prerequisite knowledge

    1. Introduction to Python

      Start coding with Python, drawing upon libraries and automation scripts to solve complex problems quickly.

    2. Jupyter Notebooks, NumPy, Anaconda, pandas, and Matplotlib

      Learn how to use all the key tools for working with data in Python: Jupyter Notebooks, NumPy, Anaconda, pandas, and Matplotlib.

      • Linear Algebra Essentials

        Learn the foundational linear algebra you need for AI success: vectors, linear transformations, and matrices—as well as the linear algebra behind neural networks.

        • Calculus Essentials

          Learn the foundations of calculus to understand how to train a neural network: plotting, derivatives, the chain rule, and more. See how these mathematical skills visually come to life with a neural network example.

          • Neural Networks

            Gain a solid foundation in the hottest fields in AI: neural networks, deep learning, and PyTorch.

        All our programs include:

        • Real-world projects from industry experts

          With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.

        • Technical mentor support

          Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you, and keeping you on track.

        • Career services

          You’ll have access to Github portfolio review and LinkedIn profile optimization to help you advance your career and land a high-paying role.

        • Flexible learning program

          Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.

        Program offerings

        • Class content

          • Real-world projects
          • Project reviews
          • Project feedback from experienced reviewers
        • Student services

          • Technical mentor support
          • Student community
        • Career services

          • Github review
          • Linkedin profile optimization

        Succeed with personalized services.

        We provide services customized for your needs at every step of your learning journey to ensure your success.

        Get timely feedback on your projects.

        • Personalized feedback
        • Unlimited submissions and feedback loops
        • Practical tips and industry best practices
        • Additional suggested resources to improve
        • 1,400+

          project reviewers

        • 2.7M

          projects reviewed

        • 88/100

          reviewer rating

        • 1.1 hours

          avg project review turnaround time

        Learn with the best.

        Learn with the best.

        • Ortal Arel

          Curriculum Lead

          Ortal Arel has a PhD in Computer Engineering, and has been a professor and researcher in the field of applied cryptography. She has worked on design and analysis of intelligent algorithms for high-speed custom digital architectures.

        • Luis Serrano

          Instructor

          Luis was formerly a Machine Learning Engineer at Google. He holds a PhD in mathematics from the University of Michigan, and a Postdoctoral Fellowship at the University of Quebec at Montreal.

        • Jennifer Staab

          Instructor

          Jennifer has a PhD in Computer Science and a Masters in Biostatistics; she was a professor at Florida Polytechnic University. She previously worked at RTI International and United Therapeutics as a statistician and computer scientist.

        • Juan Delgado

          Content Developer

          Juan is a computational physicist with a Masters in Astronomy. He is finishing his PhD in Biophysics. He previously worked at NASA developing space instruments and writing software to analyze large amounts of scientific data using machine learning techniques.

        • Grant Sanderson

          Instructor

          Grant Sanderson is the creator of the YouTube channel 3Blue1Brown, which is devoted to teaching math visually, using a custom-built animation tool. He was previously a content creator for Khan Academy.

        • Mat Leonard

          Instructor

          Mat is a former physicist, research neuroscientist, and data scientist. He did his PhD and Postdoctoral Fellowship at the University of California, Berkeley.

        • Mike Yi

          Instructor

          Mike is a Content Developer with a BS in Mathematics and Statistics. He received his PhD in Cognitive Science from the University of Irvine. Previously, he worked on Udacity's Data Analyst Nanodegree program as a support lead.

        • Juno Lee

          Instructor

          As a data scientist at Looplist, Juno built neural networks to analyze and categorize product images, a recommendation system to personalize shopping experiences for each user, and tools to generate insight into user behavior.

        • Andrew Paster

          Instructor

          Andrew has an engineering degree from Yale, and has used his data science skills to build a jewelry business from the ground up. He has additionally created courses for Udacity’s Self-Driving Car Engineer Nanodegree program.

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