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    • TensorFlow
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    • Introduction to TensorFlow for Deep Learning

    Intro to TensorFlow for Deep Learning

    BY
    TensorFlow via Udacity

    Learn practical approaches to deep learning in software development with this course on Intro to TensorFlow for Deep Learning by Udacity.

    Brochure Enquire
    • Overview
    • The highlights
    • Fee
    • Who it is for
    • Eligibility criteria
    • What you will learn
    • Admission Details
    • The syllabus
    • Scholarship
    • How it helps
    • Instructor
    • FAQs
    • Articles
    Mode

    Online

    Quick facts

    particular details
    Collaborators Google
    Medium of instructions English
    Mode of learning Self study
    Mode of Delivery Video and Text Based

    Course overview

    The Intro to TensorFlow for Deep Learning training is offered, has a rich amount of information and is instructed by three prominent instructors from TensorFlow medium. 

    The course can be pursued at self-paced progress and the candidate will learn the practicality involved with theories of deep learning for developers. The course will teach hands-on methods with models in real-world applications. The candidates will be exposed to large datasets which use advanced algorithms and techniques. The course is taught free of charge and aims to strengthen programmers and developers to build AI applications. 

    The highlights

    • Free of charge course
    • Rich learning material
    • Course taught by 3 instructors
    • Self-paced mode of learning
    • Course offered in TensorFlow medium

    Program offerings

    • Projects
    • Videos
    • Exercises

    Course and certificate fees

    certificate availability

    No

    Eligibility criteria

    Education

    The Intro to TensorFlow for Deep Learning program course does not specify any specific requirements and is intended for programmers who have good knowledge in algebra, Python, and object-oriented programming language. 

    Certification Qualification Details

    Candidates are required to complete the entire program successfully to get a certificate of completion.

    What you will learn

    Machine learning Knowledge of deep learning

    The Intro to TensorFlow for Deep Learning online course helps the candidates in the following ways.

    • Participants will get to learn about the different concepts of Machine learning with an overview of Artificial intelligence and the revolution caused by it.
    • The candidate will build a neural network in a fashion industry-based project.
    • The candidates will learn to use convolutional neural networks for the purpose of making efficient models in Fashion MNIST.
    • The students will learn transfer learning to build state-of-the-art classifiers.
    • The students will learn to save and load models using a format from TensorFlow Lite and Flowserving.
    • The student will implement forecasting of time series using sequential data and recurrent neural networks.
    • The student will work on Tensorflow Lite for smartphone applications in different forms of OS.

    Who it is for

    Computer programmer

    The Intro to TensorFlow for Deep Learning online course will help professionals such as 

    • Software Developers and programmers who want to develop apps in Artificial Intelligence (AI).

    Admission details

    Filling the form

    To register and get admission in the Intro to TensorFlow for Deep Learning certification course, students must follow the steps outlined below.

    Step 1: The following link will take you to the online program: https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187

    Step 2: Candidates should be able to register on the Udacity website and build an account.

    Step 3: The applicant must log in to the module for enrollment after entering the necessary information.

    Step 4: To understand, the applicant must be able to navigate to learn through the sequence of lectures available.

    The syllabus

    Lesson 1: Welcome to the Course

    Lesson 2: Introduction to machine learning

    Lesson 3: Your First Model - Fashion MNIST

    Lesson 4: Introduction to CNNs

    Lesson 5: Going Further With CNNs

    Lesson 6: Transfer Learning

    Lesson 7: Saving and Loading Models

    Lesson 8: Time series forecasting

    Lesson 9: NLP: Tokenization and Embeddings

    Lesson 10: NLP: Recurrent Neural Networks

    Lesson 11: Introduction to TensorFlow Lite

    Scholarship Details

    Since it is a free course, no specific information is provided; however, Udacity is committed to providing financial support to individuals in order to ensure lifelong learning and ability development, and applicants can contact Udacity officials for more information.

    How it helps

    The Intro to TensorFlow for Deep Learning certification benefits the participants in learning many aspects of programming in the areas of machine learning, deep learning, and artificial intelligence. The credential is taught by three stalwarts in this upcoming field and it thereby acts as a great identifier for the candidate being skilled in the core areas of machine learning. 

    The Udacity platform helps the candidate to share the credential in their resume or CV across many job portals and professional networks. Since machine learning and artificial intelligence is an upcoming and growing field with significant impact in the future, the candidate owing to the hands-on skills and projects in the  Intro to TensorFlow for Deep Learning certification will be well sought by recruiters in professional networking sites such as Linkedin. 

    The Intro to TensorFlow for Deep Learning online course also assists students in improving their career chances by including openings for advancement and/or higher salaries within the same business or in a different organisation. In terms of profile, the nominee would be able to gain an advantage over his peers in terms of being considered for current or future new positions.

    Instructors

    Mr Magnus Hyttsten
    Developer
    Google

    Mr Juan Delgado
    Content Developer
    Udacity

    Other Masters, Ph.D

    Ms Paige Bailey

    Ms Paige Bailey
    Developer Advocate
    Google

    FAQs

    What are the course prerequisites required to be satisfied for the student to successfully enrol into the course?

    Before the start of the programme, the candidates will need to have the most updated versions of web browsers with apps and accounts of Google and Youtube in a well-functioning operating system.

    What is the time required for the programme of the full programme?

    The Intro to TensorFlow for Deep Learning online course will be taught entirely online for a period of two months.

    What is the online link or website for the student to visit and register for the course?

    Students involved in applying can go to https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187. 

    What is the mode of instruction for this Udacity programme?

    The program's learning style is self-paced, and students will finish it whenever they choose.

    Where does a student get a copy of the program's syllabus?

    The Intro to TensorFlow for Deep Learning certification syllabus can be found on Udacity's website at https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187. 

    Does the programme include any video transcripts with instructions?

    In the structure of the programme, the students will have access to video tutorials with instructions for learning.

    How accessible are the Youtube based resources for the candidates for learning?

    Yes, Intro to TensorFlow for Deep Learning program will help the students to learn with free access to the website any time of the day.

    What kind of portfolio is required for the students to get accepted into this programme?

    Developers who have basic level expertise in seasoned programming can be benefited from this course. 

    How many instructors in total teach the certification course?

    Intro to TensorFlow for Deep Learning training has a group of three imminent instructors teaching the program for the candidates in a very comprehensive manner. 

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