Prishtina REA

The project supports the growth of Kosovo’s ICT sector by providing training courses to develop digital and business skills to support the ICT labour market and to put the improved skills effectively in use. The overall objective is to enhance the competitiveness of Kosovo’s digital and traditional business by supporting the growth of Kosovo’s ICT sector leading to growth and new job creation.

Training Modules

CYBER SECURITY PROFESSIONAL

WEB APPLICATION DEVELOPER PROFESSIONAL

WEB APPLICATION DEVELOPER PRACTITIONER

ENTERPRISE JAVA & MOBILE DEVELOPER

PYTHON PROGRAMMING

BIG DATA ANALYTICS DATA SCIENCE

MACHINE LEARNING

ARTIFICIAL INTELLIGENCE

Short description, What Learns, or Benefits will be produced from course outline

DESCRIPTION

Cybersecurity is a growing industry that needs skilled professionals to fill entry, mid, and advanced-level jobs. Cybersecurity jobs are in high demand and the demand is expected to grow by 18% over the next five years. 2022 has already become a record-breaker for the sheer volume of phishing scams, cyberattacks, data breaches and crypto heists. This Training module aims for the training of individuals who want to understand the general Cyber Security features and get practised in the main aspects of cybersecurity as in the outline as well as get hand-on experience on Offensive and Defensive Security -Ethical Hacking. This training module more focuses on the protection of organizational assets and upon completion of this module of training, you will be able to understand the details of cybersecurity mea- sures and can get employed or initiate business activity in the fields of IT Security


TARGET AUDIENCE
Individuals who have the fundamental IT Systems, Operating Systems, Net- working, It Security, Scripting, Programming, and database knowledge. Because the deep-dive activity will exist in the module applicant should have the fundamental background for the IT Systems. One year of experience in the field of IT is preferred.


     TRAINING CONTENT

  • Infrastructure security and configuration management
  • Credential management, authentication, and authorization mechanisms
  • SQL injection and defense mechanisms
  • Cross-Site Scripting (XSS), Cross-Site Request Forgery (CSRF/XSRF) protective, and
    HTTP headers
  • Digital deception
  • Introduction and Information Gathering
  • Vulnerabilities and configuration, identity, and authentication testing
  • Injection attacks Exploitation
  • Password Attacks and post-exploitation
  • Artificial Intelligence in Cyber Security

DESCRIPTION

This Training module aims for the training of individuals who want to specialise in the use of
the modern WEB Application development features including the MVC technology, APIs and
Frontend frameworks to work as a full-stack web developer. Upon completion of this
module, you will be able to start to develop modern professional looks like web applications
including the UI and Backend technologies.


TARGET AUDIENCE
Individuals having fundamental IT Systems, OS, Networking, Web technology, Design, Scripting, Programming knowledge. You should have at least one year of programming experience


     TRAINING CONTENT

  • HTML 5
  • CSS
  • Bootstrap 5
  • JAVASCRIPT
  • Ajax
  • jQuery
  • API Development
  • REACT
  • MVC

DESCRIPTION

This Training module aims for the training of individuals who want to specialise in the use of
the modern WEB Application development features including the CMS, PHP, Graphics
Design, Databases to work as a full-stack web developer. Upon completion of this module,
you will be able to start to develop modern professional looks like web applications from
scratch


TARGET AUDIENCE
Individuals having basic IT Systems, OS, Networking, Web technology, Design, Scripting,
Programming knowledge. One year of programming experience is preferred.


     TRAINING CONTENT

  • HTML 5
  • CSS
  • SEO & publishing
  • BOOTSTRAP 5
  • JAVASCRIPT
  • jQuery
  • Adobe Photoshop
  • WordPress and PHP
    in Cyber Security

DESCRIPTION

This Training module aims for the training of individuals who want to specialize in the development of Enterprise Java applications which is highly demanded by the market. The popular Java
Spring Framework will be touched on in detail to enable the full stack application development
by using Java technologies. The training on Mobile Application development by using the Kotlin
language shall improve the developer to work in the enterprises and governmental organizations. The training will combine Mobile Application development by using the Java language
which will improve the developer to develop professional mobile applications by using Java.


TARGET AUDIENCE
Individuals having basic IT Systems, OS, Networking, Web technology, Design, Scripting, Programming. At least one year of programming experience is preferred.


     TRAINING CONTENT

  • Basic Program Structure, Compilation, Tools, Console In/Out
  • Intro to Object Oriented Programming: Procedural to OO, Basic Concepts,
  • Class, Object, Interface, Modifiers"
  • Java Anonymous Classes, Anonymous Objects, Functional Interfaces, Lambda Expressions
  • Java Unit Testing
  • Java Database Connectivity: Basic Operations with famous Databases + NoSQL Databases
    (Firebase, Mondo DB)
  • Java GUI programming
  • Basic Design Patterns: Introduction, Strategies, Implementation,
    Attacks-Defenses
  • Java Threading
  • Introduction to Spring Framework, Spring Boot, JPA, Hibernate Introduction to Java Microhardness Framework (JMH)
  • Android Basic Activity UI manipulation. Using Layouts, handling screen
    Orientation
  • Android Basic Event Handling: Annotations, Listeners, Dialogs and
    Notifications
  • Passing and Receiving Data to and from Android Apps and Activities Android Sensors,
    Location Services (GPS) and Runtime Permissions Android and SQLite Databases
  • Android Audio Interaction: Speech Recognition and Text-To-Speech

DESCRIPTION

Python is currently the most widely used multi-purpose, high-level programming language. It is
used in machine learning, web development, desktop applications, and many other fields.
This Training module aims for the training of individuals who want to study with the Python
programming language has an increasing trend in the world and it is already being demanded by
the domestic market. Training shall enable the developer to become familiar with data science
features whereas to use python in all layers of the programming stack


TARGET AUDIENCE
Individuals having basic IT Systems, OS, Networking. One year of experience in the field of programming is preferred


     TRAINING CONTENT

  • Introduction to Python, Interpreter, flow control, basic types
  • Python Functions
  • Python Data Structures
  • Python Modules
  • Python In/Out
  • Python Exceptions-Exception Handling, Errors
  • Python Classes
  • Python File Handling
  • Python DB: MySQL, MongoDB
  • Python Machine Learning
  • Python – Django Framework
  • Python-Data Science

DESCRIPTION

Big data analytics helps organizations harness their data and use it to identify new opportunities.
That, in turn, leads to smarter business moves, more efficient operations, higher profits and
happier customers. Becoming a data scientist takes more than the understanding of basic skills
like statistics and programming in various languages. The need to develop one area of technical
analytic expertise while being conversant in many others is very crucial. Going beyond descriptive analytics has become essential to meet the complexities of information requirement for
decision making as well as developing strategies to drive greater profitability, improved performance and competitiveness. This course builds expertise in advanced analytics, data mining,
predictive modeling. The aim of the course is to introduce the trainees to the important big data
management techniques and analytical tools.


TARGET AUDIENCE
Individuals with fundamental knowledge on Business Intelligence, Statistics and basic knowledge
on programming with experience in Python. Having fundamental knowledge in python programming will be an advantage


     TRAINING CONTENT

  • Data Science Fundamentals
  •  Introduction to Visualization
  • Data Processing and Cleaning using Panda-Python
  •  Managing Big Data using Apache Hadoop and MongoDB
  •  Exploratory Data Analysis and Visualization
  • Data Mining using Python
  •  Data Extraction for Enterprise Reporting
  •  Advanced Analytics
  •  Linear Regression
  • Logistic Regression
  • Big Data Model Diagnostics
  • Supervised and unsupervised learning
  •  Random Forest, SVM, clustering
  •  Dimensionality reduction
  • Validation, and Evaluation of Machine Learning Methods
  • Advanced Analytic Techniques and Text Mining
  •  Simulation of sentimental analysis
  •  Optimization and Causal Mechanistic Analysis
  •  Time Series and Forecasting
  •  Big Data Security
  •  Big Data and Apache Hadoop
  •  Data Science / Big Data frameworks and RDDs
  •  SQL and Data Frames Module

DESCRIPTION

The future is driven by data, and Machine Learning (ML) makes it possible to access and analyze
larger amounts of data faster than ever before. Gartner predicts that, in next 5 years, ML will
penetrate even more business fields helping to increase efficiency and work security.
The course covers practical issues in Machine learning which includes programming in Python,
as well as a wide range of algorithms for supervised and unsupervised learning. The course will
also discuss recent applications of machine learning such as recommendation systems, email
spam detection, stock market prediction and sentiment analysis to determine the sentiment or
opinion of a given text. This course is designed to give you the practical experience you need to
quickly apply these techniques to new problems.


TARGET AUDIENCE
The course is dedicated for individuals interested in Machine Learning who have a basic understand of probabilities, statistics and algebra and fundamental background on IT Programming
with focus on python who wants to create added value to the businesses by using powerful
Machine Learning tools


     TRAINING CONTENT

  • Introduction to
  • Machine Learning
  • Naive Bayes classifier
  • Support Vector Machine
  • K-Nearest Neighbors
  • Bayesian Machine Learning
  • Bootstrap and Re-sampling methods
  • Deep Learning and Optimization techniques
  • Python programming for ML
  • Supervised Learning Techniques
  • Unsupervised Learning Techniques
  • Reinforcement Learning Techniques
  • Regression Analysis

DESCRIPTION

Artificial intelligence (AI) is the ability of a machine to display human-like capabilities such as
reasoning, learning, planning and creativity. AI is one of the fastest-growing fields in the Computer Science industry. AI is seen as central to the digital transformation of society and
it has become an EU priority.
This course provides an essential introduction to the key topics underpinning AI, including its
theoretical foundations, basic architecture, modern applications, and technical implications.
The course aims at introducing the concept of artificial intelligence and its different paradigms,
as well as at providing a good understanding of the real-world potential and limitations of AI.
Trainees will be introduced to the core concepts of programming and the practical skills involved
in producing AI-based programs to solve real-world problems, and will also explore how AI is
already being used, in different domains such as in business, healthcare and finance.


TARGET AUDIENCE
The course is dedicated for individuals interested in Machine Learning who have a basic understand of probabilities, statistics and algebra and fundamental background on IT Programming
with focus on python who wants to create added value to the businesses by using powerful
Machine Learning tools.


     TRAINING CONTENT

  • Introduction to Artificial Intelligence
  • Python programming for AI
  • Regression Analysis
  • Supervised Learning Techniques
  • Unsupervised Learning Techniques
  • Reinforcement Learning Techniques
  • Neural Networks and Deep Learning
  • Recurrent Neural Networks
  • Convolutional Neural Networks
  • Natural Language Processing (NLP) and Speech
  • Deep Learning for NLP
  • Speech recognition with Hidden Markov model (HMM) and Deep Neural Networks
  • Machine translation
  • Knowledge Representation in Expert Systems
  • Rule-based representations
  • Methodologies for building Expert Systems
  • Genetic Algorithms (GA)
  • Genetic Operators for reproduction, mutation and selection
  • Multi-objective optimization
  • Meta-heuristic algorithm

For detailed information on eligibility criteria, kindly refer to the details provided below:

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