Virtual (Google Meet)
Mentor Based
Beginners
3 weeks
About
PyTorch – Use in AI is an intensive course tailored for M.Tech, M.Sc, and MCA students, as well as E0 & E1 level professionals interested in mastering this powerful deep learning framework. The course covers PyTorch fundamentals, neural network construction, model training, and real-world applications, preparing participants to tackle complex AI challenges in various industries.
Aim
This course aims to provide an in-depth understanding of PyTorch, its applications in AI from basic concepts to advanced model architectures, and hands-on guidance on building and deploying neural network models.
Program Objectives
- Mastering PyTorch: Gain comprehensive knowledge and hands-on experience with PyTorch.
- Neural Network Proficiency: Become proficient in designing and implementing various types of neural networks.
- Practical AI Solutions: Develop practical AI solutions that can be deployed in real-world environments.
Program Structure
- Introduction to PyTorch:
- Basics of PyTorch, its comparison with other AI frameworks, and initial setup instructions.
- Building Blocks of Neural Networks:
- Detailed exploration of layers, activation functions, and the construction and debugging of neural networks.
- Training Models:
- In-depth coverage of loss functions, optimization algorithms, and effective training and validation techniques.
- Advanced PyTorch:
- Advanced topics such as convolutional and recurrent neural networks, transfer learning, and fine-tuning.
- Real-World Applications:
- PyTorch applications in industries like healthcare and autonomous vehicles, and strategies for deploying PyTorch models.
- Projects and Assessments:
- A capstone project that encompasses designing, building, and presenting a PyTorch-based AI solution.
Participant’s Eligibility
- Advanced students and professionals in M.Tech, M.Sc, and MCA programs.
- E0 & E1 level professionals in fields such as IT, BFSI, consulting, and fintech.
Program Outcomes
- Advanced PyTorch Skills: Proficiency in using PyTorch for AI model development and deployment.
- Industry Readiness: Preparedness to apply AI skills in real-world industry settings.
- Innovative Thinking: Enhanced ability to innovate in AI with the latest PyTorch techniques.
Fee Structure
Standard Fee: INR 5,998 USD 90
Discounted Fee: INR 2,999 USD 45
We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!
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Key Takeaways
Program Assessment
Certification to this program will be based on the evaluation of following assignment (s)/ examinations:
| Exam | Weightage |
|---|---|
| Mid Term Assignments | 50 % |
| Project Report Submission (Includes Mandatory Paper Publication) | 50 % |
To study the printed/online course material, submit and clear, the mid term assignments, project work/research study (in completion of project work/research study, a final report must be submitted) and the online examination, you are allotted a 1-month period. You will be awarded a certificate, only after successful completion/ and clearance of all the aforesaid assignment(s) and examinations.
Program Deliverables
- Access to e-LMS
- Real Time Project for Dissertation
- Project Guidance
- Paper Publication Opportunity
- Self Assessment
- Final Examination
- e-Certification
- e-Marksheet
Placement Assistance
- Career Guidance: Assistance with career planning and opportunities in AI development using PyTorch.
- Industry Connections: Networking opportunities with AI professionals and companies using PyTorch.
- Corporate Workshops: Real-world insights from experts actively using PyTorch in their operations.
Future Career Prospects
- AI Research Scientist: Specializing in creating innovative solutions using PyTorch.
- Machine Learning Engineer: Developing and implementing machine learning models using PyTorch.
- AI Consultant: Advising companies on integrating PyTorch into their AI strategies.
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