Free TensorFlow Certification Course [Hindi]
Welcome to our landing page dedicated to the TensorFlow course, where you’ll dive into the world of deep learning and machine learning with one of the most popular and powerful frameworks in the field.
What will you take home from DataFlair Free TensorFlow Course?
- Self-paced TensorFlow course
- 170+ hrs of study material, practicals, quizzes
- Acquire practical knowledge which industry needs
- Practical TensorFlow course with real-time case-studies
- Lifetime access with industry renowned TensorFlow certification
Why should you enroll in this Free TensorFlow course?
- Expert instructors with extensive industry experience and TensorFlow expertise
- Comprehensive curriculum covering both foundational concepts and advanced techniques
- Hands-on learning approach with coding exercises and projects
- Gain a competitive edge in the job market by acquiring sought-after skills in deep learning and TensorFlow
- Practical skills to enhance your career prospects in AI, data science, and machine learning
- Proficiency in building and training deep learning models
- Dedicated support team to assist you throughout your learning journey
- Networking opportunities with a community of fellow learners and industry experts
- Stay updated with the latest advancements in deep learning and TensorFlow
- Flexible learning schedule to fit your pace and availability
- Insight into best practices and tips for optimizing and fine-tuning models
- In-depth understanding of TensorFlow framework and its key components
TensorFlow Course Objectives
This tensorFlow course objectives are designed to provide participants with a clear roadmap to achieve their learning goals and maximize their understanding and proficiency in TensorFlow. These objectives include:
Gain a comprehensive understanding of deep learning concepts and TensorFlow framework: Participants will delve into the fundamental principles and concepts of deep learning, exploring how TensorFlow fits into the broader landscape of machine learning frameworks. They will develop a strong foundation in understanding neural networks, optimization algorithms, and model evaluation techniques.
Acquire practical skills to build and deploy machine learning models using TensorFlow: Participants will gain hands-on experience in building and training deep learning models using TensorFlow. They will learn how to leverage TensorFlow’s high-level API and flexible architecture to construct neural networks for various tasks such as image classification, natural language processing, and sequence modeling.
Bridge the gap between theory and practical implementation of deep learning algorithms: This TensorFlow course aims to equip participants with the ability to apply their theoretical knowledge of deep learning algorithms to real-world scenarios. Through practical exercises and projects, they will learn how to fine-tune models, apply transfer learning techniques, and optimize models for efficient performance.
Prepare for real-world applications and career opportunities in AI and machine learning: This TensorFlow course aims to empower participants with the skills and knowledge needed to excel in the rapidly evolving field of AI. By gaining expertise in TensorFlow, participants will be well-positioned to pursue job roles such as Machine Learning Engineer, Deep Learning Engineer, Data Scientist, and AI Developer. They will also be equipped to contribute to cutting-edge research and development in AI.
Foster a lifelong learning mindset and keep up with advancements in deep learning and TensorFlow: This TensorFlow course encourages participants to stay updated with the latest trends and advancements in deep learning and TensorFlow. By instilling a curiosity-driven mindset, participants will be motivated to continue their learning journey beyond the course, enabling them to stay at the forefront of AI innovation.
These course objectives collectively aim to empower participants with the knowledge, skills, and confidence to tackle complex AI challenges, contribute to the field of deep learning, and excel in their professional careers.
Join our TensorFlow course today and embark on an exciting journey into the world of deep learning and AI!
Why should you learn TensorFlow?
- “Deep learning will revolutionize every industry.” – Andrew Ng, AI researcher and entrepreneur.
- TensorFlow is the most widely adopted deep learning framework, used by major companies and researchers worldwide.
- According to a survey, Python and TensorFlow are the top choices for AI and machine learning development.
- TensorFlow provides a flexible and scalable platform for building and deploying deep learning models.
- TensorFlow empowers you to tackle complex tasks such as image recognition, natural language processing, and recommendation systems, allowing you to address a wide range of real-world challenges.
- TensorFlow integrates seamlessly with other popular Python libraries like NumPy and Pandas, offering a complete ecosystem for data science and AI development.
What is TensorFlow?
TensorFlow is a popular and widely adopted open-source deep learning framework developed by Google. It provides a powerful platform for building, training, and deploying machine learning models. With TensorFlow, users can leverage the flexibility and efficiency of its computational graph framework to develop and implement various deep learning algorithms. One of the key strengths of TensorFlow is its versatility. It supports a wide range of applications, including computer vision, natural language processing, speech recognition, and more. TensorFlow’s comprehensive ecosystem enables users to handle complex tasks by providing a rich set of tools, libraries, and pre-trained models. This allows developers to focus on solving high-level problems without getting lost in the intricacies of low-level implementation details. TensorFlow’s high-level API makes it accessible to b eginners and experts alike. It abstracts away complex details and provides an intuitive interface for building and training neural networks. At the same time, TensorFlow offers a lower-level interface that enables advanced users to customize and fine-tune models to meet specific requirements. Its ability to scale seamlessly across different hardware architectures, such as CPUs and GPUs, further enhances its appeal in terms of performance and efficiency. In summary, TensorFlow is a comprehensive and flexible deep learning framework that empowers developers and researchers to tackle a wide range of AI and machine learning tasks. Its extensive features, ease of use, and widespread adoption make it a go-to choice for both beginners and experienced practitioners in the field.What to do before you begin?
Before starting this TensorFlow course, it is beneficial to have a basic understanding of Python programming. Familiarity with concepts like linear algebra, calculus, and statistics will also be advantageous. While a background in machine learning or deep learning is not mandatory, a strong curiosity and eagerness to learn are essential prerequisites. This TensorFlow course curriculum covers both foundational concepts and advanced techniques, ensuring that learners can grasp the material regardless of their prior experience. Whether you’re a beginner or an experienced developer, this course will provide you with the necessary knowledge and skills to dive into the world of TensorFlow and excel in the field of deep learning.Who should go for this free TensorFlow course?
- Programmers and developers interested in AI and machine learning.
- Data scientists looking to expand their knowledge in deep learning and TensorFlow.
- Students and graduates who aspire to pursue a career in the AI industry can greatly benefit from this course, acquiring the knowledge and practical skills necessary to succeed in the field.
- Professionals who are keen to enhance their skillset and stay up-to-date with the latest advancements in deep learning will find this course highly beneficial for their career growth.
- Anyone with a passion for AI and a desire to work on exciting projects.
By enrolling in our TensorFlow course, you can expect the following benefits:
- Comprehensive coverage of deep learning concepts and TensorFlow framework
- Hands-on experience through coding exercises and real-world projects
- Interaction with industry experts and instructors for guidance and support
- Access to a vibrant community of learners and professionals for networking opportunities
- Certification upon successful completion to enhance your career prospects
- Enjoy the flexibility to learn at your own pace and convenience, allowing you to balance your learning journey with other commitments and responsibilities
- Stay abreast of the latest advancements and trends in deep learning through this course, ensuring you are equipped with the most up-to-date knowledge and techniques in the field
- Participants will develop a solid foundation in deep learning principles and gain a comprehensive understanding of neural networks, enabling them to effectively apply these concepts in real-world scenarios
- Participants will learn the methodologies and techniques for constructing and training deep learning models utilizing the TensorFlow framework
- Advanced techniques such as transfer learning, GANs, and sequence models
- Strategies for deploying and productionizing TensorFlow models
- Practical skills through project work and real-world case studies
Jobs after Learning this TensorFlow Course
- Machine Learning Engineer
- Deep Learning Engineer
- AI Researcher
- Data Scientist
- AI Developer
- Research Scientist
- Data Analyst
- AI Consultant
- Software Engineer with AI specialization
- Technical Lead in AI projects
Our students are working in leading organizations

Online TensorFlow Free Training Course Curriculum
- Understanding the basics of TensorFlow framework
- Exploring the TensorFlow ecosystem and resources
- Setting up the development environment for TensorFlow
- Introduction to neural networks and their components
- Building a basic neural network using TensorFlow
- Training neural networks with labeled datasets
- Evaluating and fine-tuning neural network models
- Understanding the principles of CNNs for image processing
- Implementing CNN architectures in TensorFlow
- Training CNNs for image classification and object detection tasks
- Applying transfer learning with pre-trained CNN models
- Leveraging pre-trained models for transfer learning
- Fine-tuning models for specific tasks and domains
- Adapting pre-trained models to new datasets
- Enhancing model performance through fine-tuning techniques
- Introduction to RNNs and their applications in sequence modeling
- Building and training RNN models using TensorFlow
- Implementing text generation and sentiment analysis with RNNs
- Exploring advanced RNN architectures like LSTM and GRU
- Understanding the principles of GANs and their applications
- Building GAN models with TensorFlow for image generation
- Training GAN models to generate realistic images
- Exploring advanced GAN architectures and techniques
- Strategies for deploying TensorFlow models in production environments
- Converting models to optimized formats for efficient deployment
- Integrating TensorFlow models into web applications and services
- Ensuring scalability and performance of deployed models
- Exploring advanced features and functionalities of TensorFlow
- Implementing custom layers and loss functions in TensorFlow
- Distributed training with TensorFlow for large-scale models
- Optimizing TensorFlow models for performance and efficiency
- Apply the knowledge and skills acquired throughout the course by working on practical projects and real-world case studies, reinforcing your understanding and providing hands-on experience.
- Working on real-world projects and use cases
- Solving challenges and implementing solutions using TensorFlow
- Gaining practical experience through hands-on project work
Real-time TensorFlow projects:
- Build Semantic Recommender System
- Self-Driving MarioKart
- Object Recognition
- Loan Eligibility Prediction
- Time Series Forecasting
Features of TensorFlow Free Course


TensorFlow Online Training FAQs
Our TensorFlow course is a comprehensive and immersive learning experience designed to equip you with the knowledge and practical skills to excel in the field of deep learning. With TensorFlow being one of the most popular and powerful frameworks in the industry, this course will empower you to harness its full potential and take your AI projects to new heights. Whether you’re a beginner or an experienced developer, this course provides a solid foundation and advanced techniques to cater to learners of all levels.
Through a combination of theoretical explanations, hands-on coding exercises, and real-world projects, you will gain an in-depth understanding of the TensorFlow framework and its key components. You will learn how to build and train deep learning models for various applications, enabling you to solve complex tasks such as image recognition, natural language processing, and recommendation systems. Moreover, you will explore advanced techniques like transfer learning, neural style transfer, recurrent neural networks (RNNs), and generative adversarial networks (GANs).
By enrolling in this course, you will have the opportunity to work on real-world projects and gain hands-on experience that directly applies to industry scenarios. Our expert instructors, who have extensive industry experience and expertise in TensorFlow, will guide you throughout the learning journey, ensuring that you receive comprehensive support and mentorship. Additionally, you will have lifetime access to the course materials and updates, allowing you to revisit the content and stay up-to-date with the latest advancements in deep learning and TensorFlow. Don’t miss this opportunity to bridge the gap between theory and practical implementation and embark on an exciting journey into the world of deep learning and AI.