Artificial Intelligence – AI

Duration: 85 Hrs

Overview

This course aims to learn the machine learning techniques on the different datasets and formation of new model with the real time applications. The new teaching methodology “teaching through entertainment” is adopted to learn the machine learning techniques.

Topics Covered

  • Python of Beginners.
  • Introduction to Python for Data Science.
  • Brushing up Python Components in terms of Statistics, data variables and structures.
  • Handling Numpy, Pandas.
  • Handling Matplotlib,Seaborn.
  • Handling Python tools for the application development.
  • Introduction to Machine, Deep learning algorithms.
  • Machine Learning Algorithm-2/Classification, Prediction and Regression.
  • Scikit-Learn For Machine learning algorithms.
  • Image Processing using OpenCV, Yolo Application.
  • Machine learning-Un-Supervisory Models- Working on Image Datasets, text datasets.
  • Machine learning Models- Artificial neural Networks.
  • Machine learning Models- Support Vector machines.
  • Machine learning Models- Random Forest/Decision Trees.
  • Machine learning Models- Naïve bayes/CART trees.
  • Machine learning Models- Ensembled Methods /Boosted Model.
  • Hybrid Learning Models for the designs- to overcome the various problems in the ML.

Audience Profile

  • Any engineers / graduates passion to learn the concepts of basic concepts of machine learning / also needs to step into their career as Data Scientist / Data Analyst.

Duration: 75 Hrs

Overview

This course aims to learn the deep learning techniques on the different datasets and formation of new model with the real time applications. The new teaching methodology “teaching through entertainment” is adopted to learn the machine learning techniques.

Topics Covered

  • Introduction to Deep learning algorithms.
  • Deep Learning Algorithm-2/Classification, Prediction and Regression.
  • Introduction to Tensor Flow -Libraries.
  • Image Processing using OpenCV, Yolo Application.
  • Convolutional Neural Networks for Image Analytics/Processing/Capsule network.
  • Working on Image Augmentation process /Working on different CNN networks.
  • NLPK-LSTM/RNN/GNU (Part-1).
  • NLPK-LSTM/RNN/GNU (Part-2).
  • Handling Time Series Data /Text Processing.
  • Transfer Learning Concepts for Image Classification.
  • Transfer Learning-Part II.
  • Federated Learning.

Audience Profile

  • Any engineers / graduates passion to learn the concepts of basic concepts of deep learning / also needs to step into their career as Data Scientist / Data Analyst.
Batch Start Date : 20th December Time : 5 PM To 7 PM (IST) Only Mon - Fri
Original Price $600 Pay now * Flexible EMI options available
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