AI and Deep Learning Analyst
Week 1-2: Introduction to Company and Role
- Introduction to the company and the role of an AI and Deep Learning Analyst.
- Familiarization with the company's robotics products and AI technologies.
- Overview of AI algorithms, deep learning models, and their applications in robotics.
Week 3-4: Programming Languages and Reading Materials
- Introduction to programming languages commonly used in AI and deep learning (Python, Java, C++, etc.).
- Assigned reading materials and research papers on AI and deep learning in robotics.
Week 5-6: Hands-on Experience with AI Models
- Hands-on experience in developing AI algorithms and deep learning models.
- Working with AI frameworks and libraries such as TensorFlow, PyTorch, or Keras.
- Collaborating with the engineering and product development teams to understand system hardware and software requirements.
Week 7-8: Experimentation and Optimization
- Participating in brainstorming sessions and contributing ideas for AI-driven robotics applications.
- Weekly progress updates and discussions with mentors.
- Collecting and analyzing large datasets for training and evaluating AI models.
- Experimenting with different deep learning architectures and techniques.
- Optimizing AI algorithms for performance and accuracy.
Week 9-10: Project Development and Presentation
- Learning about robotics and automation technologies and their integration with AI.
- Assisting in the development and improvement of the Origami AI platform.
- Participating in team meetings and discussions to contribute to project strategies optimization of system hardware and software.
- Documenting the development process, including code documentation and research reports.
- Conducting self-directed research under the guidance of mentors.
- Finalizing research reports and presentations based on the internship project.
- Presenting the internship project to the team and receiving feedback.
- Reflecting on the internship experience and sharing insights with mentors and peers.
- Conducting a self-assessment and receiving feedback from supervisors.
- Discussing potential career paths and further education in the field of AI and deep learning for robotics.