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THE CLASSES WOULD BE HELD ON SATURDAYS ONLY
COURSE COVERAGE
Course Methodology
The workshop is an interactive class with various sections touching on the basic areas of AI. It builds various pillar of learning such as presentation, discussion, application of knowledge to specific targeted areas of interest and evaluation.
Course Objectives
- Save time and money by automating routine processes and tasks
- Increase productivity and operational efficiencies
- Make faster business decisions based on outputs from cognitive technologies
- Avoid mistakes and ‘human error’, provided that smart systems are set up properly
- Use insight to predict customer preferences and offer them better, personalized experience
- Achieve cost savings, by optimizing your business, your workforce or your products
- Increase revenue by identifying and maximizing sales opportunities
Target Audience
The target audience of this course is business students and professionals interested in AI applications in data-driven business. The course is also valuable for managers who would like to make their current processes more efficient without having to dig too deep into the technology, and executives who want to use AI to obtain a competitive advantage over their competitors.
Course Outline
Introduction To Artificial Intelligence
- Introduction to Artificial Intelligence
- Data, Information, Knowledge and Intelligence
- Basic Concepts of Artificial Intelligence
- Benefits of AI
- Data Pyramid
- Property of Autonomy
- Situation Awareness
- Business Innovation with Big Data and Artificial Intelligence
- Overlapping of Artificial Intelligence with Other Fields
- Ethics and Privacy Issues
- AI and Predictive Analytics
- Application Areas
Core Machine Learning
- Machine Learning
- Machine Learning Workflow
- Learning Algorithms
- Linear Regression
- k -Nearest Neighbor
- Decision Trees
- Feature Construction and Data Reduction
- Random Forest
- k -Means Algorithm
- Dimensionality Reduction
- Reinforcement Learning
- Gradient Boosting
- Neural Network
Deep Learning
- Introduction
- Analyzing Big Data
- Different Deep Learning Models
- Auto encoders
- Deep Belief Net
- Convolution Neural Networks
- Recurrent Neural Networks
- Reinforcement Learning to Neural Networks
- Applications of Deep Learning in Business
- Business Use Case Example: Deep Learning for e-Commerce
Recommendation Engines
- Introduction
- Recommendation System Techniques
- Content-Based Recommendations
- Collaborative Recommendations
- Hybrid Approaches
- Applications of Recommendation Engines in Business
- Collection of Data
- Storing the Data
- Analyzing the Data
- Business Use Case
Natural Language Processing
- Introduction
- Morphological Processing
- Syntax and Semantics
- Semantics and Pragmatics
- Use Cases of NLP
- Text Analytics
- Sentiment Analysis
- Applications of NLP in Business
- Customer Service
- Reputation Monitoring
- Market Intelligence
Employing AI in Business
- Analytics Landscape
- Application Areas
- Complexity of Analytics
- Embedding AI into Business Processes
- Implementation and Action
- Artificial Intelligence for Growth
- AI for Customer Service
- Applying AI for Marketing
Duration: 5 Saturdays ( May 18, 25, June 1, 8, 15)
Class Session : 10:00am – 4:00pm each day including Breakfast and Lunch time
Customize Your Training
This training is currently available as residential/in-house option. If you prefer us to customize or have this training in-house at your location, kindly send your request via e-mail to:training@mctimothyassociates.com
Please Note
McTimothy Associates Reserves the right to postpone or cancel a course due to unforeseen circumstances beyond our control. In such cases delegate(s) will be registered for the next run of the Course.
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