Python is a simple, flexible and one of the most popular programming languages, which is used in almost all areas of programming: in games, creating web applications, for data analysis, for automating system administration, in machine learning, in cybersecurity, in penetration testing, in cryptography, and so on.
During the course, students will work, write programs and solve various problems and tasks through programming. They will learn to solve real analytical tasks using the Python programming language, testing and debugging, working with classes, algorithmic complexity, and data structures. Students will learn data science, Windows Forms, creating AI and smart systems, simulating rational and intuitive programs, parallel programming, working with databases and data analysis, working with the Django framework, and creating websites and applications of varying complexity.
At the end of the specialization, participants will have a final project to complete, and if successfully completed, a specialization certificate will be issued on behalf of the Scientific Cyber Security Association.
It should be noted, that Scientific Cyber Security Association will assist the successful students in the hiring process and recommend them to prospective employers.
Within the scope of the specialization, students will master the profession of a Python developer and, upon completion of the course, will be able to independently:
– evelop solutions to medium and complex tasks in Python, write programs
– Write algorithms in Python
– Work as a back-end developer
– Work as a Python developer
– Data analysis
– Start working with artificial intelligence
– Work with databases using Python
– Independently build smart systems and programs
– Program simulation of rationality and intuition
– Write desktop applications
After completing the specialization, students will have the opportunity to pass an exam on the Netacad platform and receive an international certificate from the Python Institute.
Duration of the Specialization
Price of the Specialization
1 completed project upon graduation
The training course is a way to learn the theoretical and practical application of modern standards in the field of programming. Modern, dynamic and multiparadigm language "Python" will be studied in it. which includes object-oriented, procedural, functional and imperative programming.
Course Duration: 10 Meetings/20 Hours;
Meeting 1:Why Python? Introduction to Python; How Python works; First script; Simple operations; Variables in Python; Integers; Floats; Strings; Input
Meeting 2:
If-else, elif; branching programs; random/pseudo-random numbers.
Meeting 3:
Iteration; for loop; while loop; methods for terminating and continuing a loop.
Meeting 4:
Strings; Working with strings;
Meeting 5:
Implementation and definition of functions; arguments in a function; local and global variables; function scopes.
Meeting 6:
Working with files; lists; operations on lists.
Meeting 7:
Tuples; Dictionaries; Operations on tuples and dictionaries;
Meeting 8:
ლექსიკონები, ოპერაციები ლექსი
Meeting 9:
try – except ბლოკი; შეცდომების მართვა და მისი გამოწვევა; Exeption კლასი; როგორ შევქმნათ საკუთარი Exeption კლასის მემკვიდრე; ოპერატორების გადატვირთვა.
Meeting 10:
Classes: Introduction; Examples of Classes; An Environmental Perspective on Classes; Adding Methods to Classes; Set of Integers (Class Example).
Examination
Within the course, the student will learn to solve real analytical problems using the Python programming language. The course covers: algorithms using Python, testing and debugging using Python, working with classes in Python, algorithmic complexity and data structures.
Course Duration: 10 Meetings/20 Hours;
Meeting 1:
Simple Algorithms, Bisection search; Conversion algorithms, Dealing with floats
Meeting 2:
Fractions, fraction conversion Newton Raphson
Meeting 3:
Scope in functions, scope details, key and default arguments, Built-in functions Stings recall-all methods, Recursion, Factorial
Meeting 4:
Scope in recursion
Iteration vs recursion
Mathematical induction
Tower of Hanoi
Palindromes
Meeting 5:
Fibonacci
GCD
Modules
Usage of Tuples, algorithms
Meeting 6:
Lists methods recalls, functions as objects
List of functions
Map
Algorithms with lists
Meeting 7:
Dictionaries operations recall
Leveraging dictionaries properties
Algorithms with dictionaries
Effective recursion using dictionaries
Meeting 8:
Testing and debugging
Classes of tests, testing approaches
Black box testing
Glass box testing
Bugs
Categories of bugs
Debugging in Practice
Tests
Meeting 9:
Exceptions recall, assertions
Programs with exceptions
Exception control as flow
Classes recall
Built in methods
Hierarchies
Inheritance
Algorithms with classes
Meeting 10:
Class override
Class overload
Class generators
Algorithmic complexity
Complexity classes
Recursion complexity
Searching and sorting algorithms
Extra topics: plotting and tkinter
Examination
The purpose of the course is to teach students about the current topics of Python that are widely used in practice. Within the course, you will deeply study parallel programming, databases, graphical user interface and data science. During the course, students will complete practical tasks and write different modules of real applications.
Course Duration: 10 Meetings/20 Hours;
Meeting 1:
Classes recall
Static and Class methods
Practice with inheritance
Decorators;
Meeting 2
Generators
Sqllite
Practice with Sqllite and classes;
Meeting 3:
Mongodb
Practice with Mongodb and classes;
Meeting 4:
Pyqt5
Labels, windows
Buttons, combo
Menus
Messages;
Meeting 5:
Threads
Concurrent futures
Practice
Meeting 6:
Processes
Working with multiple processes
Practice
Meeting 7:
Numpy library
Arrays
Functions
Attributes
Meeting 8:
Numpy indexes
Arithmetics
Meeting 9:
Pandas library
Working with CSV files
Dataframes and series
Adding and removing rows
Meeting 10:
Filtering
Sorting
Updating
Intro to machine learning
Examination
AI (Artificial Intelligence) is one of the fastest growing fields in computer science. It is used in various areas such as: machine learning, data analysis, automation, optimization, modeling and simulation, decision making, etc. The course starts with fundamental topics such as data structures and algorithms and includes a discussion of basic AI techniques and methods. Along with theoretical knowledge, course participants will have the opportunity to test the acquired knowledge in practical tasks. During the lecture course, students will work both independently and collaboratively, write programs and solve various standard problems, and learn to solve tasks programmatically.
Course Duration: 10 Meetings/20 Hours;
Meeting 1 - Python Lists; Dictionaries; Classes
Representing information as graphs
Meeting 2 - Functions in Python
Recursion
Meeting 3 -Solving search problems, search algorithms
DFS, BFS, gtreedy-first search A* search
Meeting 4 – Solving optimization problems, optimization algorithms
Local search; algorithms hill climbing, stimulated annealing
Meeting 5 – Continuing with optimization problems, genetic algorithms
Linear Programming
Meeting 6 – Solving Constraint Satisfaction Problems (CSPs), Game Theory
Algorithms Minimax, recursive backtracking
Meeting 7 - Machine Learning, Supervised Learning 1
Linear regression, classification,
Meeting 8 - Machine Learning, Supervised Learning 2
Decision trees, Random forests
Meeting 9 - Machine Learning, Unsupervised Learning 1
clustering, K-means
Meeting 10 - Machine Learning, Unsupervised Learning 2
hierarchical clustering, dimensionality reduction (PCA)
Examination
Django is a free (open-source) framework for creating web applications and sites. Django is written in the Python programming language. Framework - a set of tools, through which web applications and sites are created faster and easier than developing similar systems from scratch. Django has its own structure and file structure, which is developed by the so-called through the engine or core.
Course Duration: 10 Meetings/20 Hours;
Meeting 1:
Introduction in Django
Meeting 2:
Django models
Meeting 3:
Django admin
Meeting 4:
URLs and views
Meeting 5:
Django templates
Meeting 6:
Rendering in Django
Meeting 7:
Apps in Django
Meeting 8:
Model forms and Pure Django form
Meeting 9:
Form widgets and Form validation methods
Meeting 10:
Creating sample project
Examination
As part of the final project, students will use the knowledge gained in the study of specialization subjects. The final project covers practical issues from various areas of Python programming. During the project, students will be divided into groups to perform special tasks. Upon successful completion of the final project, the student receives a certificate of specialization.
Professor at Caucasus University; Head of Cyber Security; President at Scientific Cyber Security Association;
Python Developer; Lecturer at Scientific Cyber Security Association.
Python Back-End Developer at international project Normativo; Lecturer
Python Developer; Lecturer at Scientific Cyber Security Association
Price of the specialization can be paid in two installments.
Price: 1180 GEL
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