Introduction to Artificial Intelligence, Machine Learning and Deep Learning

Course Description

Artificial intelligence has become a powerful driving force in a wide range of industries, helping people and businesses create exciting, innovative products and services, enable more informed business decisions, and achieve key performance goals.

Artificial Intelligence is the ability of machines to seemingly think for themselves. AI is demonstrated when a task, formerly performed by a human and thought of as requiring the ability to learn, reason and solve problems, can now be done by a machine. A prime example is an autonomous vehicle. The vehicle is able to perceive its surroundings and make decisions in order to safely reach its destination with no human intervention. Converging technologies along with Big Data and the Internet of Things (IoT) are driving the growth of AI. Machines communicate with one another and are now capable of advanced perception, capturing millions of data points in seconds, processing the information and making decisions, all in a matter of seconds. As AI evolves, machines will have more capability to physically act based on their intelligence, eventually leading to machines that can build better versions of themselves.

The field of Artificial Intelligence (ai systems) encompasses computer science, natural language processing, math, psychology, neuroscience, data science, machine learning and many other disciplines. An introductory course in AI is a good place to start as it will give you an overview of the components bring you up to speed on the AI research and developments to date. You can also get hands-on experience with the AI programming of intelligent agents such as search algorithms, games and logic problems. Learn about examples of AI in use today such as self-driving cars, facial recognition systems, military drones and natural language processors.

This course will introduce you to the basics of AI. Topics include machine learning, probabilistic reasoning, robotics, computer vision, and natural language processing.

Who should attend:

  • Anyone interested in Artificial Intelligence, Machine Learning or Deep Learning
  • Developers aspiring to be an artificial intelligence engineer or machine learning engineer
  • Analytics managers who are leading a team of analysts 
  • Information architects who want to gain expertise in AI algorithms 
  • Analytics professionals who want to work in machine learning or artificial intelligence
  • Graduates looking to build a career in artificial intelligence or machine learning

Requirements

  • Basic computer skills
  • A passion to learn
  • Basic python is an added advantage

Duration

5 Days

Learning Outcomes

Upon completion of this course, you will understand

  • The meaning, purpose, scope, stages, applications and effects of AI
  • Fundamental concepts of machine learning and deep learning
  • The difference between supervised, semi-supervised and unsupervised learning
  • Machine Learning workflow and how to implement the steps effectively
  • The role of performance metrics and how to identify their key methods

Course Content

Module I

Introduction

  • What is AI?
  • Basics of Artificial Intelligence
  • Intelligent agents

Module II

Decoding Artificial Intelligence

  • Meaning and scope of Artificial Intelligence
  • Three Stages of Artificial Intelligence
  • Impact of AI
  • Application domains for Artificial Intelligence
  • Some real-world Applications of AI
  • Image recognition
  • Solving problems with AI

Module III

Fundamentals of Machine Learning and Deep Learning

  • Meaning of Machine Learning
  • Relationship between Machine Learning and Statistical Analysis
  • Process of Machine Learning
  • Types of Machine Learning – Supervised, Unsupervised and Semi supervised
  • Machine Learning Algorithms
    1. Regression algorithms
    2. Instance-based Algorithms
  • Deep Learning
  • Artificial Neural Networks
  • Natural Language Processing, Speech, Computer Vision

Module IV

Machine Learning Workflow

  • Gathering data
  • Data pre-processing
  • Researching the model that will be best for the type of data
  • Training and testing the model
  • Evaluation

Module V

Performance Metrics

  • What are performance metrics?
  • Need For Performance Metrics
  • Confusion matrix
  • Accuracy
  • Precision
  • Recall or Sensitivity
  • Specificity
  • F1 Score

Methodology

The instructor led trainings are delivered using a blended learning approach and comprise of presentations, guided sessions of practical exercise, web based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professionals and trainers in these fields.

All facilitation and course materials will be offered in English. The participants should be reasonably proficient in English.

Accreditation

Upon successful completion of this training, participants will be issued with a certificate of participation.

Training venue

The training is residential and will be held at T4D Training Centre in Westlands Nairobi, Kenya. The course fees cover the course tuition, training materials, two break refreshments, lunch, and study visits.

All participants will additionally cater for their, travel expenses, visa application, insurance, and other personal expenses.

Tailor- made

We can also tailor-make our courses for you. This way, you/your organization will benefit by:

  • Using own tools during the training
  • Being able to choose areas of interest you wish the trainer to put more emphasis on
  • Taking the course in-house or at a venue of choice
  • Cutting on the cost of transport and accommodation

For further inquiries, please contact us on details below: 

Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Mobile: +254 (0) 729166479

Accommodation

Accommodation is arranged upon request. For reservations contact the Training Officer.

Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Mobile Number: +254 706909947

Training fee

The course fee is KES 50,000.00 or USD 666.00 exclusive of VAT. The course fees covers the course tuition, training materials, two (2) break refreshments, lunch and study visits. Participants will cater for their travel and accommodation costs.

Payment

Payment should be transferred to Tech For Development - T4D account through bank on or before the course starting date.

Send proof of payment to This email address is being protected from spambots. You need JavaScript enabled to view it.

Cancellation policy

Payment for the all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

  1. Participants may cancel attendance 14 days or more prior to the training commencement date.
  2. No refunds will be made 14 days or less to the training commencement date. However, participants who are unable to attend may opt to attend a similar training at a later date, or send a substitute participant provided the participation criteria have been met

Please Note: The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.

Event Properties

Event Date 02-12-2019 8:00 am
Event End Date 06-12-2019 5:00 pm
Capacity 100
Cut off date 02-12-2019
Individual Price USD666.00
Location T4D Training Center
We are no longer accepting registration for this event
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+254 706909947

  outreach@t4d.co.ke

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  Gate 18, 1st Floor, W6.

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