Artificial Intelligence & Machine Learning with Python

Course Overview

Artificial intelligence is the recreation of human insight through machines. Machine learning is a connected insights or arithmetic. It is a subfield of software engineering.

If you are a computer geek, if you love coding and wish to explore dimensionless world of programming, TechTrunk brings you the core Artificial Intelligence Training which will take you through core development and programming experience and will make you expert in writing algorithms for AI applications, you will learn Machine Learning, Linear Regression, Artificial Neural Network, Support Vector Machine and much more.

Course Objective

Toward the finish of this course, you will have the capacity to

  • Identify potential zones of uses of AI
  • This course covers foundational concepts and hands-on learning of leading machine learning tools, such as Python, Linear Regression, Support Vector Machine, Artificial Neural Network and more.

Tools:

Prerequisites:

Candidate must have basic knowledge of any programing language and a basic idea of Mathematics.

Software to be installed –

Anaconda – https://www.anaconda.com/download/ (According to bit version 32 bit for 32 Machine and 64 bit for a 64-bit machine)
Machine Requirement:
Recommended – Machine with 4GB RAM, i3 or above quad-core processor
Requirement: Working Internet Connection throughout the training for participants.
Python Libraries used (Most of them are already available in Anaconda, others we will install during the training)

FAQ’S

How can we do practice?

We are providing hand on training, we use to provide all coding guideline for your practice

How can we resolve our queries?

We are providing 24*7 Technical support till 3 Months, for any query you may reach on support@techtrunk.in

Do you provide any Certificate for this course?

Yes, Course Certificate from TechTrunk Ventures

Consider the possibility that I miss a class?

You can experience the recorded session of the missed class that is accessible for web-based review through the LMS.

 

Course Curriculum

  • Basics of AI & Introduction

    • AI Introduction
      30m
  • Python Programming

    • Introduction to Python Programming Language
      0m
    • Data Structure & Data Manipulation in Python
      0m
    • Visualization in python
      0m
  • Mathematical modelling- Machine Learning

    • Linear Regression
      0m
    • Decision Trees
      0m
    • Naïve Bayes
      0m
    • Logistic Regression
      0m
  • Artificial Neural Networks

    • Neurons, ANN & Working
      0m
    • Single Layer Perceptron Model
      0m
    • Multilayer Neural Network
      0m
    • Feed Forward Neural Network
      0m
    • Cost Function Formation
      0m
    • Applying Gradient Descent Algorithm
      0m
    • Backpropagation Algorithm & Mathematical Modelling
      0m
    • Programming Flow for backpropagation algorithm
      0m
    • Use Cases of ANN
      0m
    • Programming SLNN using Python
      0m
    • Programming MLNN using Python
      0m
    • Digit Recognition using MLNN
      0m
    • XOR Logic using MLNN & Backpropagation
      0m
    • Diabetes Data Predictive Analysis using ANN
      0m
    • Project – Banking Problem Analysis – When the customer will leave?
      0m
    • Project – Medical Problem Analysis
      0m
  • Support Vector Machine

    • Concept and Working Principle
      0m
    • Mathematical Modelling
      0m
    • Optimization Function Formation
      0m
    • The Kernel Method and Nonlinear Hyperplanes
      0m
    • Use Cases
      0m
    • Programming SVM using Python
      0m
    • Character recognition using SVM
      0m
    • Regression problem using SVM
      0m
    • Wisconsin Cancer Detection using SVM
      0m
  • Image Processing with Opencv

    • Image Acquisition and manipulation using opencv
      0m
    • Video Processing
      0m
    • Edge Detection
      0m
    • Corner Detection
      0m
    • Face Detection
      0m
    • Image Scaling for ANN
      0m
    • Training ANN with Images
      0m
    • Character Recognition
      0m
  • Clustering

    • Hierarchical Clustering
      0m
    • K Means Clustering
      0m
    • Use Cases for K Means Clustering
      0m
    • Programming for K Means using Python
      0m
    • Image Color Quantization using K Means Clustering Technique
      0m
  • Principle Component Analysis

    • Dimensionality Reduction, Data Compression
      0m
    • Concept and Mathematical modelling
      0m
    • Use Cases
      0m
    • Programming using Python
      0m
  • Introduction to TensorFlow-Deep Learning

    • The Programming Model
      0m
    • Data Model
      0m
    • Tensor Board
      30m
    • Introducing Feed Forward Neural Nets
      0m
    • Softmax Classifier
      0m
    • ReLU Classifier
      0m
    • Dropout Optimization
      0m
    • Deep Learning Applications
      0m

Instructors

Admin bar avatar

A Technical expert and a passionate trainer has expertise in the field of Internet of Things and Machine Learning, Technical Training and Project Management, he has a proven work record of delivering Technical Training in various technologies and domains at the premier organizations.. He has delivered 50+ corporate Training to clients from India and abroad.

INTERNET OF THINGS
• Corporate Clients – UST Global, mphasis, Accenture, UST Global, CompuCom etc,
• Guest Speaker at 3+ International Conferences and Summits on IoT, Smart City Development and Technological Advancements.
• Designed Course material for online courses on IoT, AI & Machine Learning
• Worked 3+ Industrial IoT Projects

ARTIFICIAL INTELLIGENCE & MACHINE LEARNING
• Corporate Clients – Kronos, HARMAN, mphasis, Accenture, Ericsson, UTC etc,
• Delivered Online training on Machine Learning, Artificial Intelligence and Internet of things to clients from Saudi Countries, South Africa, Bangladesh & US
• Delivered 100+ Lectures across pan India including IIT Roorkee, IIT Kanpur, IIT Jodhpur, IIT Chennai, IIT Bhubaneswar, NIT Sikkim, NIT Surathkal etc.
• Machine learning techniques and algorithms: Good practical experience on complex data for recommendation process, churn and classification, using Random forest, SVM, K-NN, Neural Network, and other decision tree techniques (CHAID, CART)

Santosh has around 18 years of IT experience, out of which and more than 14 years’ experience in Application Design, managing and Development focuses in SAP, Data Science and E-commerce. He has around 11 years of Service/Project/Program Management across various continents (Europe, Americas and Asia). Worked on ASAP and Agile implementation Methodology.
He is having real-time experience on AI & Machine Learning, He is having 10+ Year experience in IBM Industry

Reviews

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    January 16, 2018 at 04:23 am

    This course assisted me understand the basic to advanced of AI & Machine Learning Professional Program and boosted my skills to become a qualified professional in my field.- SAI

    January 1, 2018 at 11:23 am

    Awesome quality of Training.. Thanks

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