Tenserflow for Data Science Training

Welcome to our comprehensive TensorFlow for Data Science Course, where we explore the powerful capabilities of TensorFlow for building and deploying machine learning models. TensorFlow is an open-source machine learning framework developed by Google that provides a flexible ecosystem for building and deploying machine learning models at scale. In this course, you'll learn how to leverage TensorFlow to perform a wide range of data science tasks, from building basic neural networks to deploying complex deep learning models in real-world applications. Ready to unlock the full potential of TensorFlow for data science and machine learning? Enroll in our TensorFlow for Data Science Course today and embark on a journey towards becoming a proficient TensorFlow practitioner.

Tenserflow Course in Pune

What will You learn?

  1. Introduction to TensorFlow: Understand the fundamentals of TensorFlow and its role in the field of data science and machine learning.
  2. Building Neural Networks with TensorFlow: Learn how to build and train neural networks using TensorFlow's high-level APIs, including Keras.
  3. Deep Learning with TensorFlow: Explore advanced deep learning techniques such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs) using TensorFlow.
  4. Deploying TensorFlow Models: Learn how to deploy TensorFlow models in production environments using TensorFlow Serving, TensorFlow Lite, and TensorFlow.js.
  5. TensorFlow Extended (TFX): Understand how TensorFlow Extended can be used for end-to-end machine learning workflows, including data validation, preprocessing, model training, evaluation, and serving.

Why choose our course?

  1. Comprehensive Curriculum: Our course covers all the essential topics and techniques you need to know to kickstart your journey in data science, from data wrangling and exploratory analysis to machine learning and statistical modeling.
  2. Hands-On Learning: Get hands-on experience with real-world datasets and practical projects that reinforce your understanding of key concepts and techniques, and develop the skills needed to tackle real-world data science challenges.
  3. Expert Instruction: Learn from industry experts and experienced data scientists who bring real-world insights and expertise to the classroom, and receive personalized guidance and feedback throughout your learning journey.
  4. Flexible Learning Options: Our course is designed to accommodate learners of all levels, from beginners to experienced professionals looking to upskill, with flexible scheduling options and self-paced learning resources to fit your busy lifestyle.

Who is this course for?

  1. Aspiring Data Scientists: Individuals looking to start a career in data science and gain the foundational knowledge and practical skills needed to succeed in the field.
  2. Business Professionals: Professionals in fields such as marketing, finance, and healthcare who want to leverage data science techniques to drive business insights and decision-making and stay ahead of the curve in their industries.
  3. Students: Students studying fields like computer science, mathematics, or statistics who want to supplement their academic studies with practical skills in data science and gain a competitive edge in the job market.

Course Syllabus

  • Understanding the fundamentals of TensorFlow and its role in data science and machine learning
  • Exploring the TensorFlow ecosystem: TensorFlow Core, TensorFlow Extended (TFX), TensorFlow.js, and TensorFlow Lite
  • Overview of TensorFlow's high-level APIs: Keras and TensorFlow Estimators
  • Understanding TensorFlow computation graphs and their role in defining and executing TensorFlow operations
  • Creating and manipulating TensorFlow graphs using TensorFlow's Python API
  • Introduction to TensorFlow sessions for executing computational graphs and performing computations
  • Overview of neural networks and their architecture
  • Implementing feedforward neural networks (multilayer perceptrons) using TensorFlow
  • Training neural networks with TensorFlow using gradient descent and backpropagation
  • Understanding convolutional neural networks (CNNs) and their applications in image classification and object detection
  • Implementing CNNs using TensorFlow's high-level APIs (Keras) for tasks such as image classification and object recognition
  • Training and fine-tuning CNNs using TensorFlow for various computer vision tasks
  • Introduction to recurrent neural networks (RNNs) and their applications in sequence modeling and time series prediction
  • Implementing RNNs using TensorFlow's high-level APIs (Keras) for tasks such as text generation and sentiment analysis
  • Training and fine-tuning RNNs using TensorFlow for sequence modeling tasks
  • Understanding transfer learning and its applications in machine learning
  • Leveraging pre-trained models and fine-tuning them for specific tasks using TensorFlow
  • Implementing transfer learning and fine-tuning techniques using TensorFlow's high-level APIs (Keras)
  • Overview of TensorFlow Serving and its role in serving machine learning models in production environments
  • Deploying TensorFlow models using TensorFlow Serving for scalable and efficient model serving
  • Managing and monitoring TensorFlow Serving deployments for model inference

Contact Us

Career Opportunities in data science

Frequently Asked Questions

    Yes, at Guidance Point, we offer a dedicated course in TensorFlow as part of our comprehensive data science program. This course focuses on understanding and implementing machine learning and deep learning models using TensorFlow, one of the most popular deep learning frameworks.

    While a basic understanding of Python programming and familiarity with machine learning concepts can be beneficial, there are no strict prerequisites for enrolling in the TensorFlow course. Our instructors tailor the curriculum to accommodate students with varying levels of experience.

    Our TensorFlow course is seamlessly integrated into the data science curriculum, offering dedicated modules that cover topics such as building neural networks, training models, and deploying them for various applications in data science.

    Absolutely. Practical application is a key component of our TensorFlow course. Students have the opportunity to work on hands-on projects and assignments that involve implementing machine learning and deep learning models using TensorFlow on real-world datasets.

    Yes, our TensorFlow course is designed to equip students with a comprehensive understanding of TensorFlow principles and techniques. By the end of the course, students should feel confident in their ability to use TensorFlow to build and deploy machine learning and deep learning models for various data science applications.

Tenserflow for Data Science



Courses At Guidance Point

Guidance Point provide wide range of course in multiple domains with 44+ training courses with some of them with job assistance.