Artificial Intelligence and Digital Assistants in Professional Activities

Person responsible

Dr. Janara Baitugelova .,
Prof. Bekejanov M., Researcher Osmonova
B.

Duration
of the module

1 semester

Semester

2

Frequency
of the module

Every
semester

ECTS Credits (CP)

4 CP

Semester
hours per week, number of weeks

2/ 16

Workload

X h (4 * 30 h)

Contact hours: 48

Self-study: …72

Module
type

Elective
Course

Required prerequisites for
the module

Module Prerequisites
:

<![if !supportLists]>·
<![endif]>Basic computer and internet skills.

<![if !supportLists]>·
<![endif]>Proficiency in Office programs (Word, Excel, PowerPoint
).

<![if !supportLists]>·
<![endif]>Ability to use email and cloud services.

Recommended
prior knowledge for the module

Recommended prerequisites for this module

<![if !supportLists]>·
<![endif]>General understanding of
digital technologies and information systems.

<![if !supportLists]>·
<![endif]>Basic knowledge of computer
science, logic, and algorithms.

<![if !supportLists]>·
<![endif]>Understanding the principles
of artificial intelligence at the user level (eg, chatbots , voice assistants, recommendation systems).

Teaching language

Russian and English

Competencies
gained /

Learning
outcome

Acquired competencies / Learning
outcomes

Students are able to:

• apply artificial intelligence technologies and digital assistants
  in professional activities;
• analyze the possibilities and limitations of using AI tools in
  various fields;
• select and use appropriate digital services to automate tasks,
  search for information, and improve work efficiency;
• develop simple scenarios for interaction with virtual assistants
  and chatbots;
• critically evaluate the ethical and legal aspects of the use of
  AI.

On based on :

• studying the principles of artificial intelligence, machine
  learning and natural language processing;
• analysis of practical cases and examples of the use of digital
  assistants in various industries;
• mastering AI tools (ChatGPT, Copilot , Gemini , Siri , Alexa , etc.) in
  educational and professional tasks.

By means of :

• lectures, demonstrations and practical classes with digital
  assistants;
• implementation of individual and group projects;
• practical problem solving using AI
  platforms;
• interactive discussions, tests and presentations.

Contents of the module

Module Contents

This module
provides students with theoretical knowledge and practical skills in using
artificial intelligence technologies and digital assistants in their
professional work.
Students will become familiar with AI principles, modern tools, and services,
and learn how to apply them to solve real-world problems.

Main thematic
sections module :

<![if !supportLists]>1.
<![endif]>Basics
artificial intelligence

<![if !supportLists]>o <![endif]>The concept, history and development
directions of AI.

<![if !supportLists]>o <![endif]>Key technologies: machine learning,
neural networks, natural language processing.

<![if !supportLists]>o <![endif]>Ethical and legal aspects of using AI.

<![if !supportLists]>2.
<![endif]>Digital
assistants

<![if !supportLists]>o <![endif]>Types and functions of digital assistants
(chatbots, voice assistants, intelligent decision support systems).

<![if !supportLists]>o <![endif]>Review of popular assistants: ChatGPT , Google Assistant
, Siri
, Alexa
, Copilot
, etc.

<![if !supportLists]>o <![endif]>Setting up, interacting with, and
integrating assistants into professional activities.

<![if !supportLists]>3.
<![endif]>Practical
application of AI

<![if !supportLists]>o <![endif]>The use of AI tools in education,
business, marketing, medicine, and other industries.

<![if !supportLists]>o
<![endif]>Automate
routine tasks and increase productivity with AI.

<![if !supportLists]>o <![endif]>Development of mini-projects using
digital assistants.

Applicability
of the module

Relevant
curriculum (s)

The module can be included in the following
educational programs:

<![if !supportLists]>·
<![endif]>Informational technologies

<![if !supportLists]>·
<![endif]>Digital transformation and management data

<![if !supportLists]>·
<![endif]>Business Informatics

<![if !supportLists]>·
<![endif]>Pedagogy and digital education

<![if !supportLists]>·
<![endif]>Economics and
Management (in terms of digital competencies)

<![if !supportLists]>·
<![endif]>Tourism and
services (in terms of the use of AI for customer interaction
and data analysis)

Requirements for the award of credit points

(Study and exam requirements)

Requirements for earning credit points (training and
examination requirements)

To successfully
complete the module and earn credit points, students must meet the following
requirements:

<![if !supportLists]>1.
<![endif]>Attendance
and activity :

<![if !supportLists]>o <![endif]>mandatory participation in at least 80% of classes (lectures and practical work);

<![if !supportLists]>o <![endif]>active participation in discussions,
demonstrations and practical tasks;

<![if !supportLists]>o <![endif]>maintaining academic integrity and
discipline.

<![if !supportLists]>2.
<![endif]>Current
(benchmark) assessment :

<![if !supportLists]>o <![endif]>completion of individual and group
assignments;

<![if !supportLists]>o <![endif]>preparing mini-projects or presentations
using AI tools;

<![if !supportLists]>o <![endif]>participation in tests, quizzes or
practical tests.

Total
weight​ rating : 50%

<![if !supportLists]>3. <![endif]>Final certification
(exam/project defense):

<![if !supportLists]>o <![endif]>defense of the final project
demonstrating the practical application of digital assistants;

<![if !supportLists]>o <![endif]>oral or written testing on theoretical
questions of the course;

<![if !supportLists]>o
<![endif]>grade level formed competencies
.

Total
weight​ rating: 50%

<![if !supportLists]>4.
<![endif]>Criteria
assessments :

<![if !supportLists]>o <![endif]>completeness and quality of assignments;

<![if !supportLists]>o <![endif]>originality and practical value of
solutions;

<![if !supportLists]>o
<![endif]>competent use of AI tools ;

<![if !supportLists]>o <![endif]>ability to argue and present the results
of work.

Learning
and teaching types

Types of learning and
teaching

Types of teaching:
• Lectures with multimedia presentations and demonstrations of AI tools; •
Training in seminars and interactive classes; • Practical exercises using
digital assistants (ChatGPT
, Copilot , Gemini ,
etc.);
• Work on individual and group projects; • Discussions and analysis of cases
from professional practice.

Types of training:
• Self-paced learning program on an educational platform (online materials,
video tutorials , tests);
• Training with an instructor and mentor in person or online; • Completion of
research and creative assignments; • Reflection and self-assessment of the
learning outcomes obtained.

Training formats:
• Asynchronous self-paced online
learning — study of theoretical materials, completion of
online assignments and tests at a convenient time;
• Synchronous online and
face-to-face classes — participation in lectures,
practical seminars, presentations and discussions in real time, office hours;

• Blended learning (blended learning ) is a combination of distance and
classroom forms aimed at developing digital and communication skills.

Literature (latest editions) and other
instruction material

References:

<![if !supportLists]>· <![endif]>Kolmogorova, S. S. Fundamentals of Artificial Intelligence: A
Textbook for Students / S. S. Kolmogorova. — Saint
Petersburg: SPbGLTU, 2022. — 108 p.

<![if !supportLists]>· <![endif]>Arshinsky, L. V. Methods and Algorithms of
Artificial Intelligence: A Textbook / L. V. Arshinsky, T. K. Kirillova. -
Irkutsk: IrGUPS, 2022. — 124 p.

<![if !supportLists]>· <![endif]>Fundamentals of Artificial Intelligence: A Textbook
/ Yu. A. Antokhina, A. A. Ovodenko, M. L.
Krichevsky, Yu. A. Martynova. — Saint Petersburg: GUAP, 2022. — 169 p.

<![if !supportLists]>· <![endif]>Okrepilov, V. V. Fundamentals of Artificial
Intelligence in Professional Activity: a tutorial / V. V. Okrepilov, A. S. Stepashkina, E. A. Frolova. — St. Petersburg: GUAP, 2022.
— 153 p.

Recommended Internet resources

<![if !supportLists]>·
<![endif]>Section 1. Basics artificial intelligence

https://stepik.org/course/58 303

https :// www . coursera . org / learn / ai — for — everyone

<![if !supportLists]>·
<![endif]>Section 2. Digital assistants

https://chat.openai.com

https://yandex.ru/alice/

https://assistant.google.com

<![if !supportLists]>·
<![endif]>Section 3. Practical application of AI

https://copilot.microsoft.com

https :// www . notion . so / product / ai

https :// openai . com / education

Sample projects and topics for
independent work

Sample projects and topics for
independent work

1. Individual projects :

• Developing a scenario for interaction with a
  digital assistant to solve a professional problem (for example,
  automating responses to frequent customer requests).
• Analyze the possibilities of using ChatGPT,
  Copilot or Gemini in your future profession.
• Creation of a mini-presentation «The role
  of artificial intelligence in the modern economy / education / tourism /
  medicine».
• Development of a training module using AI tools
  (e.g., generation of tasks, texts, illustrations).
• Research into the ethical aspects of AI
  application in a specific area (e.g. data protection, plagiarism,
  transparency of decisions).

2. Group projects :

• Create a chatbot for educational or
  informational purposes (e.g. «College Assistant» or
  «Syllabus Assistant»).
• Developing a plan for implementing digital
  assistants in an organization (school, office, travel agency, etc.).
• Analysis and comparison of digital assistants (Siri, Alexa , ChatGPT , Copilot , etc.) by
  functionality and applicability.
• Preparing a video presentation or infographic
  «How AI is changing the profession of the 21st century
  .»

3. Independent Job includes :

• Preparation of short essays, analytical reviews
  and presentations on the chosen topic;
• Studying online courses or interactive
  materials on the application of AI;
• Carrying out tasks on setting up and testing
  digital assistants;
• Reflection (report) on one’s own experience of
  interacting with AI tools.