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Artificial Intelligence

Artificial Intelligence

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Recorded content
Of Total 10 Hrs.
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Duration
3 Months (50 hours)
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LIVE sessions
4 Workshops
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Hands-On Learning
With Practice Modules
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Certificate
With License

React Components

Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think.

AI is accomplished by studying how human brain thinks, and how humans learn, decide, and work while trying to solve a problem, and then using the outcomes of this study as a basis of developing intelligent software and systems.

Objective

  • Learn the fundamental theory behind neural networks
  • Model an arbitrary function using an artificial neural network (ANN)
  • Practice interpreting loss metrics and convergence conditions
  • Apply a neural net to a regression problem
  • Understand regularization within the context of ANNs
  • Construct 2D convolutional image classification architectures
  • Perform a multi class classification
  • Apply Deep Learning to sequential data using recurrent architectures (RNNS, LSTMs and GRUs)
  • Implement dropout and LASSO as network regularization strategies
  • Apply Deep Learning to a classification problem
  • Implement image processing methods in Python and Keras
  • Extend feed-forward network architectures to convolutional layers
  • Apply Deep Learning to time series forecasting applications
Join Next Batch Starting on September 10th

Outline

Artificial Intelligence (AI) is a cutting-edge field of computer science that focuses on creating computer systems and algorithms capable of mimicking human intelligence. These systems are designed to learn from data, reason, make decisions, and solve complex problems.

AI encompasses various subfields, including machine learning, natural language processing, computer vision, and robotics. AI applications range from virtual assistants like Siri to self-driving cars and advanced medical diagnostics.

Configuration management in Artificial Intelligence (AI) involves the systematic management and control of various components and settings within AI projects. It is crucial for maintaining consistency, reproducibility, and efficiency throughout the AI development lifecycle.

Training Materials

All Deep Learning training students receive comprehensive courseware.

Software Requirements

The software requirements for Artificial Intelligence (AI) are essential tools and libraries that enable the development, training, and deployment of AI models and applications. Python is the predominant programming language, supported by powerful machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn. Data manipulation and analysis rely on libraries like Pandas and NumPy, while Matplotlib and Seaborn aid in data visualization. Integrated development environments (IDEs) like Jupyter Notebook and version control systems like Git enhance code development and collaboration.. Containerization with Docker ensures consistency, and cloud platforms like AWS and Google Cloud offer scalable resources. GPU support via CUDA and cuDNN accelerates deep learning tasks, and specialized libraries for Natural Language Processing (NLP) and Computer Vision (e.g., NLTK, spaCy, OpenCV) cater to specific AI domains.

Why Online Bootcamps

Develop skills for real career growth

Cutting-edge curriculum designed in guidance with industry and academia to develop job-ready skills

Learn by working on real-world problems

Capstone projects involving real world data sets with virtual labs for hands-on learning

Learn from experts active in their field, not out-of-touch trainers

Leading practitioners who bring current best practices and case studies to sessions that fit into your work schedule.

Structured guidance ensuring learning never stops

24x7 Learning support from mentors and a community of like-minded peers to resolve any conceptual doubts