Exploring AI & Machine Learning for the Enterprise Overview (with Light Hands-on) is a basic, primer-level course designed to provide you with a solid ‘first-look’ at essential AI and machine learning technologies, related cutting-edge skills, and the innovative tools that support them, with a focus on how they are applied in business in a practical way. These transformative technologies offer paths to enhance decision-making, quickly modernize and improve operational efficiency, and drive innovation within your organization. Our engaging AI practitioner will guide you through useful lectures, valuable demonstrations and group discussions, along with light-hands-on activities working with some of the core skills and tools. Throughout the course, you’ll learn what AI is and isn't, differentiating between AI, Machine Learning and Deep Learning, and what’s happening with trending Large Language Model use. You’ll also examine processing language, images, and audio with AI.

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* Actual course outline may vary depending on offering center. Contact your sales representative for more information.

Learning Objectives

Throughout the course you’ll:
Gain a clear introduction to the exciting world of AI and Machine Learning, along with current trends and tools, enabling you to participate confidently in strategic discussions and help to make informed decisions.
Get a hands-on introduction to a few user-friendly tools and skills offering you a taste of the practical side of AI and Machine Learning.
Explore the practical business applications of AI and Machine Learning in an everyday context, and the potential influence of these technologies on your organization.
Learn the basics about algorithms, NLP, Neural Networks, GPT, Generative AI and other innovative tools, and how
Explore how AI plays a pivotal role in processing language, images, and audio
Learn how organizations maximize use of these technologies to their benefit to improve processes and maximize efficiencies

1

  • INTRODUCTION TO AI & MACHINE LEARNING

  • Understand what AI and Machine Learning are and why they're critical for modern business

    Exploring definitions and types of AI

    Discussing AI in the Modern Age and its role in business

    Embrace Change: Learn and Build Confidence using theTools – Don’t be Replaced By Them

2

  • DEEPER DIVE INTO MACHINE LEARNING

  • Basics of how mathematics are used in or apply to AI

    Algorithms: What are they and how are they used in AI and ML

    Supervised vs Unsupervised

    Classification, Regression, Clustering, Dimensionality Reduction, and Ensemble Methods

    The role of Machine Learning in AI and business decision-making

    Demo: Algorithms in Action

    Case study: Review a real business scenario where Machine Learning was used to increase efficiency.

3

  • LEVERAGING AI IN BUSINESS & DECISION MAKING

  • Discussing key business areas where AI adds value: Operations, Marketing, Sales, HR, content development, coding and software development

    Explore how AI is used in business decision-making

    Introduction to predictive analytics

    Using AI for strategic decisionmaking

    Demo & Review: Explore different AI tools used in businesses and the results achieved.

4

  • HOT TRENDS FOR AI IN BUSINESS: LARGE LANGUAGE MODELS (LLM), GENERATIVE AI AND GPT

  • Understand the basics of Generative AI and how it differs from other AI techniques

    Introduction to GPT and its applications in various sectors

    Explore how GPT uses machine learning to generate human-like text based on the input it receives.

    Understand the concept of language models and how they are trained using large amounts of text data

    Lab: Solve Business Problems with a GPT based tool and discuss its implications.

5

  • BASICS OF NEURAL NETWORKS

  • What are they and how are they used?

    Basic parts: Neurons, activation functions, interactions.

    Types: Feedforward, recurrent, convolutional neural networks overview.

    How they learn: Forward propagation, backpropagation explained.

    Training Neural Networks: Importance of data preprocessing in training.

    Deep Neural Networks: Advantages and practical applications overview.

    In Action: Image recognition, language processing, etc. use cases.

    Ethical Considerations: Addressing biases and ethical concerns in neural networks.

6

  • NATURAL LANGUAGE PROCESSING (NLP) & SENTIMENT ANALYSIS

  • What is NLP and how is it used?

    NLP Language and Semantic Meaning, Bigrams, Trigrams, nGrams, Root Stemming and Branching

    Introduction to Sentiment Analysis: Sentiment indicators, Sentiment Sampling, Predicting Elections based on Sentiment Analysis

    Lab: Use an online sentiment analysis tool to analyze customer feedback from a popular business

7

  • USING AI FOR IMAGE, VIDEO, AND AUDIO PROCESSING

  • Learn about Image processing and Identification, Facial Analysis, Audio Processing

    Discuss the role of AI in analyzing streaming video and real-world AV processing

    Lab: Use AI in recognizing and analyzing images

8

  • AI FOR BUSINESS TECHNICAL TOOLS: DATA SCIENCE, DEEP LEARNING & THE CLOUD

  • Applying AI in Data Science overview

    Tools: Python, NumPy, Pandas, SciKitLearn, Hadoop, Spark

    NoSQL Databases

    Deep Learning overview

    Tools: Tensorflow, Keras, NLTK

    AI for Business in the Cloud overview

    Tools: Azure, Google, IBM, Amazon solutions

9

  • PRACTICAL APPLICATIONS AND THE FUTURE OF AI IN BUSINESS

  • What's next in applied AI for businesses

    New AI trends shaping the future of business

    Ethical considerations when implementing AI

Audience

This course is ideally suited for a wide variety of technical learners just getting started with AI or machine Learning, seeking a primerlevel overview of these technologies, skills and related tools. Attendees might include: Developers aspiring to be a 'Data Scientist' or Machine Learning engineers Analytics Managers who are leading a team of analysts Business Analysts who want to understand data science techniques Information Architects who want to gain expertise in Machine Learning algorithms Analytics professionals who want to work in machine learning or artificial intelligence Graduates looking to build a career in Data Science and machine learning

Language

English

Prerequisites

Experienced professionals who would like to harness machine learning in their fields to get more insight about customers Students attending this class should have a grounding in Enterprise computing. While there’s no particular class to offer as a prerequisite, students attending this course should be from a somewhat technical background, and familiar with Enterprise IT, have a general (high-level) understanding of systems architecture, as well as some knowledge of the business drivers that might be able to take advantage of applying AI. Basic knowledge of Python scripting is also helpful but not required. The hands-on labs in this course may leverage some basic Python scripts as needed, but the labs can be completed in a ‘follow-along’ format, under the guidance of the instructor. Prior experience with Python can be helpful but is not necessary.

$1,895

Length: 2.0 days (16 hours)

Level:

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