Machine Learning, AI, and Deep Learning

Enhance your skills in Machine Learning and Artificial Intelligence

Course Code : 0114

$2895

Overview

Cognixia’s Machine Learning, Artificial Intelligence and Deep Learning training course covers the latest machine learning algorithms while also talking about the common threads that can be used in the future for learning a wide range of algorithms. The course is a complete package that will help learners build their skillsets and meet the demand of the ML-AI industry, going beyond the theoretical concepts of the technology like regression, clustering and classification, and discussing their applications as well.

Schedule Classes

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Course Delivery

This course is available in the following formats:

Live Classroom
Duration: 16 days

Live Virtual Classroom
Duration: 16 days

What You'll learn

  • Overview of Machine Learning, Artificial Intelligence and Deep learning
  • Supervised and unsupervised learning concepts and modelling
  • Solving business problems using Artificial Intelligence and Machine Learning
  • Various theoretical concepts and how they relate to the practical aspects of machine learning and AI
  • Application of concepts such as regression, clustering, classification, dimensional reduction and engine recommendation

Outline

  • What is Machine Learning?
  • Machine Learning use-cases
  • Machine Learning process flow
  • Machine Learning categories
  • What is AI?
  • Applications of AI
  • History of AI
  • Inductive Reasoning and Deductive Reasoning
  • What is included in AI? (Robotics, Agents and more)
  • Installing and setting up – R and R Studio
  • Fundamentals: Vector, function, packages
  • Matrices: Building, naming dimensions, operations, visualizing, sub-setting
  • Data Frames: Building, merging, visualizing (ggplot2)
  • Hands-on/Lab exercises
  • Data analysis pipeline
  • What is Data Extraction?
  • Types of Data
  • Raw and processed data
  • Data wrangling
  • Exploratory data analysis
  • Visualization of data
  • Loading different types of datasets in R
  • Arranging the data
  • Plotting the graphs
  • Hands-on/Lab exercises
  • Supervised and unsupervised learning
  • Simple linear regression
  • Multiple linear regression
  • Support vector machine
  • Hands-on/ Lab exercises
  • Classification
  • What is a decision tree?
  • Algorithm for decision tree induction
  • Creating a perfect decision tree
  • Confusion matrix
  • What is a Random Forest?
  • What is a Navies Bayes?
  • Support vector machine: Classification
  • Hands-on/ Lab exercises
  • What is Clustering? (Including use-cases)
  • What is K-means Clustering?
  • What is C-means Clustering?
  • What is hierarchical Clustering?
  • Hands-on/ Lab exercises
  • Feature extraction with PCA
  • Feature selection techniques
  • What are association rules and their use cases?
  • What are recommendation engines and how do they work?
  • Types of recommendation types
  • User-based recommendation
  • Item-based recommendation
  • Difference: User-based and item-based recommendation
  • Recommendation use-case
  • Hands-on/ Lab exercises
  • What is time series data?
  • Time series variables
  • Different components of time series data
  • Visualizing the data to identify time series components
  • Implementing ARIMA model for forecasting
  • Exponential smoothing models
  • Identifying different time series scenario based on which different Exponential Smoothing model can be applied
  • Implementing respective ETS model for forecasting
  • Hands-on/ Lab exercises
  • What is Deep Learning?
  • Biological Neural Networks
  • Understanding Artificial Neural Networks
  • Building an Artificial Neural Network
  • How does ANN work?
  • Important terminologies of ANN
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Prerequisites

A sound understanding of programming languages such as R and Python will be beneficial, however, not mandatory.

Who Should Attend

Cognixia’s Machine Learning, AI, and Deep Learning course is highly recommended for:

  • Data scientists or a Machine Learning experts
  • Software and Application Developers
  • Business Analysts/Analytics professionals
  • Recent graduates looking to build a career in Artificial Intelligence
  • Technology enthusiasts with a sound understanding of Machine Learning
  • Software Architects or Software Engineers who wish to gain expertise in Machine Learning algorithms

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Certification

Participants will be awarded with an exclusive certificate upon successful completion of the program. Every learner is evaluated based on their attendance in the sessions, their scores in the course assessments, projects, etc. The certificate is recognized by organizations all over the world and lends huge credibility to your resume.

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