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    "# Welcome to AI for Science Bootcamp\n",
    "\n",
    "The objective of this bootcamp is to give an introduction to application of Artificial Intelligence (AI) algorithms in Science ( High Performance Computing(HPC) Simulations ). This bootcamp will introduce participants to fundamentals of AI and how those can be applied to different HPC simulation domains. \n",
    "\n",
    "The following contents will be covered during the Bootcamp :\n",
    "- [CNN Primer and Keras 101](Intro_to_DL/Part_2.ipynb)\n",
    "- [Steady State Flow using Neural Networks](CFD/Start_Here.ipynb)"
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    "## [CNN Primer and Keras 101](Intro_to_DL/Part_2.ipynb)\n",
    "\n",
    "In this notebook, participants will be introduced to Convolution Neural Network and how to implement one using Keras API. For an absolute beginner to CNN and Keras this notebook would serve as a good starting point.\n",
    "\n",
    "**By the end of this notebook you will:**\n",
    "\n",
    "- Understand the Machine Learning pipeline\n",
    "- Understand how a Convolution Neural Network works\n",
    "- Write your own Deep Learning classifier and train it.\n",
    "\n",
    "For in depth understanding of Deep Learning Concepts, visit [NVIDIA Deep Learning Institute](https://www.nvidia.com/en-us/deep-learning-ai/education/)"
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    "## [Steady State Flow using Neural Networks](CFD/Start_Here.ipynb)\n",
    "\n",
    "In this notebook, participant will be introduced to how Deep Learning can be applied in the field of Fluid Dynamics.\n",
    "\n",
    "**Contents of this notebook:**\n",
    "\n",
    "- Understanding the problem statement\n",
    "- Building a Deep Learning Pipeline\n",
    "    - Understand data and task\n",
    "    - Discuss various models\n",
    "    - Define Neural network parameters\n",
    "- Fully Connected Networks\n",
    "- Convolutional models\n",
    "- Advanced networks\n",
    "\n",
    "**By the end of the notebook participant will:** \n",
    "\n",
    "- Understand the process of applying Deep Learning to Computational Fluid Dynamics\n",
    "- Understanding how Residual Blocks work.\n",
    "- Benchmark between different models and how they compare against one another.\n",
    "\n",
    "## Licensing\n",
    "This material is released by NVIDIA Corporation under the Creative Commons Attribution 4.0 International (CC BY 4.0)"
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