Exploring AI and Machine Learning for the Enterprise | Hands On (AA-TTML5502)


Course Description

Learn the foundations of Artificial Intelligence (AI), including its sub-fields, and how it can be applied in modern business. This course introduces AI from a practical business perspective.

Course Outline

Artificial Intelligence

  • Definitions of AI
  • Types of AI
  • Mathematics in AI
  • Deep and Wide learning
  • AI and SciFi
  • AI in the Modern Age

Machine Learning

  • Supervised vs. Unsupervised
  • Classification
  • Regression
  • Clustering
  • Dimensionality Regression
  • Ensemble Methods

Expert Systems

  • Rules Systems
  • Feedback loops
  • RETE and beyond
  • Expert Systems in practice

Neural Networks

  • Neural Networks
  • Recurrent Neural Networks
  • Long-Short Term Memory Networks
  • Applying Neural Networks

Natural Language Processing

  • Language and Semantic Meaning
  • Bigrams, Trigrams, and n-Grams
  • Root stemming and branching
  • NLP in the world

Image, Video, and Audio Processing

  • Image processing and Identification
  • Facial Analysis
  • Audio Processing
  • Analyzing Streaming Video
  • Real-world AV processing

Sentiment Analysis

  • Sentiment: The beginnings of emotional understanding
  • Sentiment indicators
  • Sentiment Sampling
  • Algorithmic Trading on Sentiment
  • Predicting Elections

Current Tools of the Trade

  • Python, NumPy, Pandas, SciKit
  • Hadoop and Spark
  • NoSQL Databases
  • TensorFlow, Keras, and NLTK
  • Drools

Whatís Next in AI

  • Current Developments
  • Gazing at the Crystal Ball

Course Objectives

Join an engaging hands-on learning environment, where youíll learn:

  • What AI is and what it isnít
  • The different types and sub-fields of AI
  • The differences between Machine Learning, Expert Systems, and Neural Networks
  • The latest in applied theory
  • How AI is used in processing language, images, audio, and the web
  • The current generation of tools used in the marketplace
  • Whatís next in applied AI for businesses

This course has a 40% hands-on labs to 60% lecture ratio with engaging instruction, demos, group discussions, labs, and project work.

Course Prerequisites

To gain the most from this course, you should have:

  • A grounding in enterprise computing
  • Familiarity with enterprise IT
  • A high-level understanding of systems architecture
  • Knowledge of your business drivers that could take advantage of AI
  • Basic knowledge of scripting

Course Information

Length: 2 day

Format: Lecture and Lab

Delivery Method: n/a

Max. Capacity: 16



Schedule

Contact Us


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1-877-797-2799
info@firefly.cloud

Labs

  • Hands-On Format: This course is extended to add hands-on machines based labs. These hands-on classes have a high lab to lecture ratio, combining engaging lecture, demos, group activities and discussions with comprehensive machine-based practical programming labs and project work.


Who Should Attend

Business Analysts, Data Analysts, Developers, Administrators, Architects, Analytics Managers, and technical Executives who are new to AI.