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Home Data Science Data Science Courses TENSORFLOW – Specialization | 16 Course Series | 2 Mock Tests

TENSORFLOW
Specialization | 16 Course Series | 2 Mock Tests

This TensorFlow Certification includes 16 Courses with 63+ hours of video tutorials and One year access and several mock tests for practice. You get to learn TensorFlow for Deep Learning with Python. We will help you learn to build a neural network and how to train, evaluate and optimize it with TensorFlow.

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4.5 (17,239 ratings)

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What you'll get

  • 63+ Hours
  • 16 Courses
  • Mock Tests
  • Course Completion Certificates
  • One year access
  • Self-paced Courses
  • Technical Support
  • Mobile App Access
  • Case Studies
  • Download Curriculum

Synopsis

  • Courses: You get access to all 16 courses in the Projects bundle. You do not need to purchase each course separately.
  • Hours: 63+ Video Hours
  • Core Coverage: TensorFlow for Deep Learning with Python
  • Course Validity: One year access
  • Eligibility: Anyone serious about learning Machine Learning and wants to make a career in this Field
  • Pre-Requisites: Basic knowledge about machine learning would be preferable
  • What do you get? Certificate of Completion for each of the 16 courses, and projects
  • Certification Type: Course Completion Certificates
  • Verifiable Certificates? Yes, you get verifiable certificates for each course with a unique link. These link can be included in your resume or LinkedIn profile to showcase your enhanced skills
  • Type of Training: Video Course – Self Paced Learning

Content

  • MODULE 1: Tensorflow Essentials Training

    Courses No. of Hours Certificates Details
    Machine Learning ZERO to HERO - Hands-on with Tensorflow13h 39m✔
    Project on Tensorflow - Implementing Linear Model with Python1h 46m✔
    Project on Tensorflow: Face Mask Detection Application33m✔
  • MODULE 2: Deep Learning

    Courses No. of Hours Certificates Details
    Deep Learning: Neural Networks with TensorFlow3h 11m✔
    Deep Learning ZERO to HERO - Hands-on with Python11h 17m✔
    Deep Learning Tutorials1h 34m✔
    Pandas with Python Tutorial5h 42m✔
    NumPy and Pandas Python5h 9m✔
    Pandas Python Case Study - Data Management for Retail Dataset3h 14m✔
    Matplotlib for Python Data Visualization - Beginners4h 2m✔
    Matplotlib for Python Data Visualization - Intermediate2h 53m✔
    Matplotlib for Python Data Visualization - Advanced6h 37m✔
  • MODULE 3: Learning from Seaborn

    Courses No. of Hours Certificates Details
    Seaborn Python - Beginners2h 28m✔
    Seaborn Python - Intermediate1h 18m✔
    Seaborn Python - Advanced1h 56m✔
    Case Studies on Seaborn Python Basics1h 51m✔
  • MODULE 4: Mock Tests & Quizzes

    Courses No. of Hours Certificates Details
    Test - TensorFlow Exam
    Test - Test Series TensorFlow

Description

  • The set of skills that can be acquired upon completion of this TensorFlow training are Data Analysis, TensorFlow, Deep Learning Application, Numpy, Pandas, Matplotlit, Seaborn, Conda Environment, Data Visualization, and Data Processing, etc.
  • The TensorFlow course contains also several chapters in the courses and few chapters under each course which was covered in the course curriculum are such as the installation of TensorFlow, Introduction of TensorFlow, different data types in TensorFlow, PyCharm IDE environment setup, etc.
  • There are few skills also which could be obtained in completing this course are such as TensorFlow Model, Neural Networks, PyCharm IDE, TensorFlow Eager API, Linear regression, Logistic regression, and TensorFlow, etc.
  • The TensorFlow certification also contains a set of tangible skills which are advanced Deep Learning Applications, Statistical Analysis, different mathematical models for prediction analysis, etc.
  • This TensorFlow course is very useful for the prospective ML Developers, Machine Learning Engineer, Software Developer, Python Developer, Web Development, etc.

Sample Certificate

Course Certification

Requirements

  • Willingness to pursue a career as a Machine Learning Engineer or Analytics Engineer or Hadoop Developer: The TensorFlow training does not contain any prerequisites and can be preferred by any learner to master the basic concepts or knowledge on Machine Learning, Deep learning, data analytics tools, data processing techniques using PyCharm IDE, etc. All the learners who are interested to learn the TensorFlow concepts such as installation and setup of deep learning model using TensorFlow library and python programming etc. Data Analysis and Data Visualization techniques can also be carried out using different tools using the TensorFlow library which is explained in this course. The basic core concepts of the TensorFlow library are explained clearly in the course contents and description. This course can also be learned with any basic knowledge of mathematics or computer science or any basic programming skills or Data analytics or processing tools related technologies.
  • Knowledge in Data Analytics or Hadoop or Big Data Tools: Any previous knowledge or hands-on in the areas of Data Analytics or Big Data Development or Hadoop Development or data analytics tools is an added advantage in further learning the contents of the TensorFlow training. This course as several advantages upon learning the core and advanced concepts such as data analysis, TensorFlow library, handling and processing large volumes of data, multiple and parallel operations on large amounts of data in an efficient manner. There are also a lot of benefits to learning the concepts of this TensorFlow course.

Target Audience

  • Students of Mathematics or Computer programming or Statistical background: The learners who are holding any Bachelor’s engineering in Computer Science or any technical areas can choose this TensorFlow training as a better option in getting expertise in Deep Learning technologies. All the learners who are keen in learning and obtaining knowledge on Deep Learning techniques or Data processing or Big data analytics or Hadoop frameworks can opt for this TensorFlow course. This TensorFlow training is beneficial and added advantage to master the latest technologies in the technological career or profession with greater benefits to their career and profession. This TensorFlow certification is well recommended to all the prospective learners who are very much interested to learn the latest Data Analysis tools and techniques. This TensorFlow training is designed in a basic and advanced way to cover all the fresh and experienced learners to secure greater job opportunities.
  • Analytics Engineer Scientist or Hadoop Developer or Data Architect: The learners of this TensorFlow training will be able to master a lot of basic to advanced concepts in the area of Deep Learning data processing techniques or Data analytics tools or Hadoop related big data concepts, and digital data tools, several Python tools such as PyCharm IDEs and TensorFlow like libraries are added as the contents of this course which are of greater importance in the area of Machine Learning and also adds a lot more benefits to the prospective learner’s career as a Data Analyst, Data Scientist, Software Development Engineer, Software Developer, Research Scientist, Data Analyst, Business Analyst, Hadoop Developer, Researcher, SAS Programmer, R Programmer, Machine Learning Engineer, Machine Learning Developer, AI Expert, Chatbots Developer, AI ML Engineer, Python Developer, Python ML Engineer, Solution Architect, Machine Learning Scientist, etc. This course can opt also to pursue better career opportunities in the area of Machine Learning or Deep learning processes.
  • Bachelor / Master’s Degree in Technology: Any learner with Bachelor or Master Degree holder in the technology area can opt for this Edu CBA – TensorFlow course to become a Machine Learning Engineer or Analytics Engineer or Big Data Developer or Data Architect or Specialist in the larger multinational companies.

Course Ratings

  • Michael Williams
    Perfect Pandas Primer

    I enjoyed this tutorial. It seemed to be very up-to-date. The instructors were clear, concise, and thorough. The structure was intuitive and presented in an understandable manner, building on each step and using data frames and sets that avoided confusion by using names that didn't sound like operational commands and vice versa. Grammar and logic were exceptional, with very little wasted time. A great introduction to using Pandas.

    Michael Williams

  • Prashant Nookala
    Good course to kickstart

    Good course to kickstart with Python & Pandas. Very well explained by the trainer. Practical aspect is very well covered along the basics. Although it is a bit slow, but it helps in better understanding of the concept. I would certainly recommend this to the the ones who are willing to learn kick-start Python & Pandas.

    Prashant Nookala

  • Greg Kowalczyk
    Deep Learning

    I got this link while searching over internet, I have gone through If you want to learn Neural Nets and TensorFlow, then this course is perfect. It helped me a lot to understand basic things in Machine Learning. Very detailed explanation with examples helped me to get through each sections. Looking forward to more such training.

    Greg Kowalczyk

* One Time Payment & Get One year access

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Course Curriculum
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    CoursesNo. of Hours
    Machine Learning ZERO to HERO - Hands-on with Tensorflow13h 39m
    Project on Tensorflow - Implementing Linear Model with Python1h 46m
    Project on Tensorflow: Face Mask Detection Application0h 55m
    Deep Learning: Neural Networks with TensorFlow3h 11m
    Deep Learning ZERO to HERO - Hands-on with Python11h 17m
    Deep Learning Tutorials1h 34m
    Pandas with Python Tutorial5h 42m
    NumPy and Pandas Python5h 9m
    Pandas Python Case Study - Data Management for Retail Dataset3h 14m
    Matplotlib for Python Data Visualization - Beginners4h 2m
    Matplotlib for Python Data Visualization - Intermediate2h 53m
    Matplotlib for Python Data Visualization - Advanced6h 37m
    Seaborn Python - Beginners2h 28m
    Seaborn Python - Intermediate1h 18m
    Seaborn Python - Advanced1h 56m
    Case Studies on Seaborn Python Basics1h 51m

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