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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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.
