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Artificial Intelligence, AI


Ensure your career success with this Artificial Intelligence program.  This program is a blend of Artificial Intelligence, Data Science, Machine Learning, and Deep Learning, enabling the real-world implementation of advanced tools and models. This AI certification course is designed to give you in-depth knowledge of Artificial Intelligence concepts including the essentials of statistics required for Data Science, NLP using Javascript programming, and Machine Learning. Through these AI courses, you will learn how to develop deep learning, and essential Machine Learning techniques, such as supervised and unsupervised learning, advanced concepts covering artificial neural networks, and layers of data abstraction and TensorFlow.

Artificial intelligence and Machine Learning will impact all segments of daily life by 2025, with applications in a wide range of industries such as healthcare, transportation, insurance, transport and logistics, and customer service. A role in this domain places you on the path to an exciting, evolving career that is predicted to grow sharply into 2025 and beyond.


Our AI Training Bundle includes:

  • Artificial Intelligence Learn How To Build An AI
  • Deep Learning and Computer Vision OpenCV, SSD & GANs
  • Artificial Intelligence & Machine Learning for Business
  • Tensorflow Deep Learning and Artificial Intelligence
  • Conversational AI (Chatbots) and NLP using Javascript
  • Modern Artificial Intelligence Masterclass: Build Projects


What you will learn:

  • Artificial Neural Networks (ANNs) / Deep Neural Networks (DNNs)
  • Predict Stock Returns
  • Time Series Forecasting
  • Computer Vision
  • How to build a Deep Reinforcement Learning Stock Trading Bot
  • GANs (Generative Adversarial Networks)
  • Recommender Systems
  • Image Recognition
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)
  • Use Tensorflow Serving to serve your model using a RESTful API
  • Use Tensorflow Lite to export your model for mobile (Android, iOS) and embedded devices
  • Use Tensorflow's Distribution Strategies to parallelize learning
  • Low-level Tensorflow, gradient tape, and how to build your own custom models
  • Natural Language Processing (NLP) with Deep Learning
  • Demonstrate Moore's Law using Code
  • Transfer Learning to create state-of-the-art image classifiers
  • Understand the concepts of NLP, NLU, NLG, NER and how they are applied
  • Understand Artificial Intelligence writing regressions in javascript using Brain and Tensorflow
  • Write your own tokenizer and use existing tokenizers from Natural and NLPjs
  • Write NLU classifiers in javascript using Brain, Tensorflow, NLPjs Neural, Microsoft LUIS
  • Build your own Perceptron in javascript from scratch and your own NLU Classifier
  • Measure the precision of the different NLPs using a custom corpus and SIGDIAL22
  • Understand what is stemming, apply stemmers to the classifiers that you built (Brain, Tensorflow, NLPjs neural, Microsoft LUIS, and your own classifier),
  • Different KPIs for NLU: Machine Learning Measures, Confidence, Clarity, TPS, Language Support
  • Named Entity Recognition: enum entities, regular expressions, builtins using Microsoft Recognizers and Duckling (extract emails, URLs, dates, numbers...)
  • Useful NLP Algorithms: utterance generation from patterns, N-Grams, Language Prediction, Predictive Text, Levenshtein distance, get best similar substring, emoji replacement
  • How to build your own chatbot, benchmark it, do it multi-language, publish into console, add a web for talking with the chatbot
  • Deploy Emotion AI-based model using Tensorflow 2.0 Serving and use the model to make inference.
  • Understand the concept of Explainable AI and uncover the BlackBox nature of Artificial Neural Networks and visualize their hidden layers using GradCam technique.
  • Develop Deep Learning model to automate and optimize the brain tumor detection processes at a hospital.
  • Build and train AI model to detect and localize brain tumors using ResNets and ResUnet networks (Healthcare applications).
  • Understand the theory and intuition behind Segmentation models and state-of-the-art ResUnet networks.
  • Build, train, deploy AI models in business to predict customer default on credit card using AWS SageMaker XGBoost algorithm.
  • Optimize XGBoost model parameters using hyperparameters optimization search.
  • Apply AI in business applications by performing customer market segmentation to optimize marketing strategy.
  • Understand the underlying theory and mathematics behind DeepDream algorithm for Art generation.
  • Develop, train, and test State-of-the-art DeepDream algorithm to create AI-based art masterpieces using Keras API in TF 2.0.
  • Develop ANNs models and train them in Google’s Colab while leveraging the power of GPUs and TPUs.


Why become an AI Engineer?

The current and future demand is staggering. The New York Times reports a candidate shortage for certified AI Engineers, with fewer than 10,000 qualified people in the world to fill these jobs, which according to Paysa earn an average salary of $172,000 per year in the US for AI Engineers with the required skills.


Who should take this Artificial Intelligence course?

With the demand for AI in a broad range of industries, our AI certification course is well suited for a variety of roles and disciplines, including:

  • Developers aspiring to be an Artificial Intelligence Engineer or Machine Learning Engineer
  • Analytics Managers who are leading a team of analysts
  • Information Architects who want to gain expertise in Artificial Intelligence algorithms
  • Analytics professionals who want to work in machine learning or artificial intelligence
  • Graduates looking to build a career in Artificial Intelligence and machine learning
  • Experienced professionals who would like to harness Artificial Intelligence in their fields to get more insight



Program Components

  • Artificial Intelligence Learn How To Build An AI
  • Deep Learning and Computer Vision OpenCV, SSD & GANs
  • Artificial Intelligence and Machine Learning for Business
  • Tensorflow Deep Learning and Artificial Intelligence
  • Conversational AI (Chatbots) and NLP using Javascript
  • Modern Artificial Intelligence Project Builds



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