Web Programming with AspNet Core MVC

About Education

This course is aimed at software developers who want to learn how to develop modern web applications under the ASP.NET Core MVC framework. Participants gain in-depth knowledge of Model-View-Controller (MVC) architecture, data access with Entity Framework Core, authentication and authorization (ASP.NET Identity), dynamic HTML generation with Razor syntax, API development, dynamic operations with JavaScript, and different layers of web applications. At the end of this application-focused course, participants will be equipped to develop .NET-based web solutions at the enterprise level.

Prerequisites

• Basic knowledge of C#
• HTML, CSS and basic JavaScript knowledge
• Have basic knowledge of database structures and SQL
•  

Duration of Training

Toplam Süre: 5 Gün (Günde 6 saat)
Toplam Eğitim Saati: 30 saat
Eğitim Formatı: Uygulamalı ve interaktif yüz yüze /online ortam

Who Should Participate?

• Software developers who want to enter the field of web development
• Those who want to develop enterprise applications using .NET technologies
• Developers who want to transition from frameworks such as NET Web Forms, PHP, and Java
• Software engineering or computer engineering students
• All software developers who want to work on the .NET platform as full-stack developers

Educational Content

1. Application Development with MVC Architecture

• What is the MVC Pattern?
• Creating Controller, View and Model
• Controller Methods and View Transitions
• Search Feature, Add New Field and Validation
• Details and Deletion Operations

2. Data Access with Entity Framework Core (EF Core)

• Introduction to EF Core and Package Installation
• Creating Entity and DbContext
• Updating the Database with Migrations
• Integrated Use with MVC
• SQL Server Type Mapper and Transaction Management

3. Authentication and Authorisation with ASP.NET Identity

• Authentication
• Individual User Accounts and Roles
• 2 Factor Authentication
• Authorisation

4. Request Processing with Controller

• Routing and Model Binding
• Model Validation
• File Upload Processes
• Dependency Injection Kullanımı
• Controller Tests

5. HTML Generation with Razor

• Razor View Syntax and Compilation
• Layouts, HTML, and Tag Helpers
• Partial Views
• Using DI (Dependency Injection) in View

6. Dynamic Interaction with JavaScript

• Using JavaScript and jQuery
• Data Exchange with AJAX
• Partial Update Scenarios

7. ASP.NET Core Fundamentals

• Application Startup and Middleware Structure
• Static Files, Routing, URL Rewrite
• Error Handling
• Real-Time Data with SignalR
• Globalization & Localization
• Configuration, Logging, Environment Management
• Session and Application State Management

8. Web API Development

• Developing RESTful APIs with API Controller
• Minimal API Usage
• HTML and JSON Formats
• Security Layers and Client Application Communication

9. ASP.NET Core Server Technologies

• Kestrel, ASP.NET Core Module, WebListener
• OWIN ve Request Features
• ASP.NET vs ASP.NET Core Comparison

What You Will Gain at the End of Training

• Developing modern web applications with the NET Core MVC architecture
• Managing database operations with Entity Framework Core
• Identity verification, authorisation and user management
• Building service-based architectures by developing Web APIs
• Creating dynamic user interfaces with MVC + Razor + JavaScript
• Learn about the NET Core infrastructure, middleware structure, and hosting options.

Implementing a SQL Data Warehouse 2019 Training

About Education

Bu eğitim, modern veri ambarı çözümlerinin SQL Server 2019 altyapısıyla nasıl tasarlanıp hayata geçirileceğini öğrenmek isteyen profesyonellere yöneliktir. Eğitim boyunca veri ambarı mimarisi, boyutsal modelleme, ETL süreçleri, SSIS kullanımı, veri kalitesi ve ana veri yönetimi gibi konular ele alınacak; ayrıca Azure SQL Data Warehouse çözümleriyle bulut entegrasyonu da uygulamalı olarak incelenecektir. Katılımcılar, kurumsal veri ambarı çözümlerinin uçtan uca planlanması, geliştirilmesi ve yönetilmesi konusunda yetkinlik kazanacaktır.

Prerequisites

• SQL Server üzerinde temel veri tabanı bilgisi (tablolar, sorgular, ilişkiler vb.)
• T-SQL sorgulama bilgisi (SELECT, JOIN, GROUP BY, vb.)
• Temel düzeyde SSIS bilgisi avantaj sağlar, ancak zorunlu değildir
• Daha önce “Querying SQL Server” veya “Administering SQL Server” eğitimlerinden birini almış olmak önerilir

Duration of Training

Toplam Süre: 5 Gün (Günde 6 saat)
Toplam Eğitim Saati: 30 saat
Eğitim Formatı: Uygulamalı ve interaktif yüz yüze/online ortam

Who Should Participate?

• BI (Business Intelligence) uzmanları ve veri mühendisleri
• SQL Server geliştiricileri ve veritabanı yöneticileri
• Veri ambarı projelerinde görev alan analistler ve yazılımcılar
• SQL Server Integration Services (SSIS) ile ETL geliştirenler
• Kurumsal düzeyde veri yönetimi, raporlama ve analiz altyapılarını kurmak isteyen tüm IT profesyonelleri

Educational Content

1. Introduction to Data Warehousing

• Veri ambarı nedir? Ne zaman ve neden kullanılır?
• Veri ambarı çözümü için temel mimari ve planlama yaklaşımı

2. Planning Data Warehouse Infrastructure

• Altyapı planlamasında dikkat edilmesi gerekenler
• Donanım ve performans ihtiyaçlarının analizi

3. Designing and Implementing a Data Warehouse

• Boyutsal modelleme yaklaşımları
• Dimension ve Fact tablolarının tasarımı
• Fiziksel veri ambarı yapılarının kurgulanması

4. Columnstore Indexes

• Columnstore indekslerin avantajları
• Oluşturma ve yönetim adımları
• Performans üzerinde etkisi ve kullanım senaryoları

5. Implementing an Azure SQL Data Warehouse

• Azure platformunun veri ambarı avantajları
• Azure SQL Data Warehouse kurulumu ve geliştirme adımları
• Azure Data Factory ile veri taşıma ve entegrasyon

6. Creating an ETL Solution

• SSIS ile ETL kavramına giriş
• Kaynak verinin analiz edilmesi
• Veri akışı (Data Flow) bileşenleriyle dönüşüm süreçlerinin uygulanması

7. Implementing Control Flow in an SSIS Package

• SSIS paketlerinde akış kontrolü (Control Flow)
• Dinamik paketler oluşturma, konteyner kullanımı
• Veri tutarlılığı sağlama yöntemleri

8. Debugging and Troubleshooting SSIS Packages

• Paket hata ayıklama teknikleri
• SSIS loglama mekanizmaları
• Hata işleme stratejileri

9. Implementing a Data Extraction Solution

• Artımlı veri çekme (Incremental ETL)
• Değişen verinin tespiti ve yükleme işlemleri
• Temporal tablolarla versiyon kontrolü

10. Enforcing Data Quality

• Veri kalitesi nedir? Neden önemlidir?
• Data Quality Services (DQS) kullanımıyla veri temizleme ve eşleştirme

11. Master Data Services

• MDS kavramı ve temel kullanım alanları
• Hiyerarşiler ve koleksiyonlar
• Ana veri merkezi (Master Data Hub) kurulumu

12. Extending SQL Server Integration Services

• SSIS paketlerinde script kullanımı
• Özel bileşenlerle SSIS genişletme

13. Deploying and Configuring SSIS Packages

• SSIS proje dağıtımı
• Paket çalıştırma planlaması ve izleme

14. Consuming Data in a Data Warehouse

• BI ve raporlama kavramlarına giriş
• Azure SQL Data Warehouse ile analiz uygulamaları
• Raporlama çözümleriyle entegrasyon

What You Will Gain at the End of Training

• SQL Server 2019 üzerinde veri ambarı tasarım prensiplerini kavrama ve uygulama
• Fact ve dimension tabloları doğru şekilde tasarlayabilme
• SSIS ile profesyonel düzeyde ETL paketleri oluşturabilme ve yönetebilme
• Azure SQL Data Warehouse’a geçiş süreci, veri taşıma ve analiz konularında uzmanlaşma
• Veri kalitesi süreçleri ve Master Data Services (MDS) ile merkezi veri yönetimi altyapısı kurma
• Veri ambarındaki verilerin raporlanması ve analizinde en iyi uygulamaları öğrenme

SQL Server 2019 Management Training

About Education

This training provides comprehensive information and practical applications for the effective installation, management, monitoring, and protection of Microsoft SQL Server 2019 by system administrators and database administrators (DBAs). Throughout the training, advanced administrative topics such as SQL Server installation, configuration, backup and restore strategies, security, monitoring, data transfer, automation, replication, and high availability will be covered using practical examples. Participants will gain the knowledge and skills necessary to manage SQL Server infrastructures securely, reliably, and efficiently.

Prerequisites

• Basic knowledge of SQL (T-SQL query proficiency)
• Familiarity with database concepts
• Basic proficiency in Windows Server environments
• Previous training in ‘Querying SQL Server’ or similar courses is advantageous.

Duration of Training

Toplam Süre: 5 Gün (Günde 6 saat)
Toplam Eğitim Saati: 30 saat
Eğitim Formatı: Uygulamalı ve interaktif yüz yüze/online ortam

Who Should Participate?

• Database administrators (DBAs)
• System administrators and IT infrastructure specialists
• Technical team members who manage SQL Server in production environments
• Candidates who have set SQL Server administration as their career goal
• Application developers, individuals seeking to better understand data infrastructure

Educational Content

1. SQL Server Installation and Configuration

• SQL Server ön gereksinimleri
• SQL Server kurulumu ve yönetimi
• Measuring service configuration and hardware requirements
• SQLIOSIM usage and installation automation

2. Database and File Management

• Database planning and creation
• File/FileGroup management
• Metadata review, file transfer
• Buffer Pool Extension configuration

3. Disaster Recovery (Backup & Restore)

• Backup strategies
• Transaction log architecture
• Full, differential, and transaction log backup
• Restore operations, time-based rollback
• Snapshots, system database recovery

4. SQL Server Security and Authorisation

• Security model, user and role management
• Encryption, keys and certificates
• Fixed/database roles and custom role definition
• Authorisation levels and schema-based control

5. Monitoring and Performance Tracking

• Current Activity & System Monitor
• Data Collector and SQL Profiler
• DDL triggers, Event Notification
• Audit mechanisms and warning systems

6. Data Transfer

• Data transfer architecture
• Import/Export Wizard and SSIS usage
• ETL processes with SSIS, distribution, bcp tool

7. Database Maintenance

• Data integrity checks
• Index maintenance, file size management
• Scheduling automatic maintenance tasks

8. Advanced Management Tools

• Policy-Based Management
• Multi-server management
• Resource Governor kullanımı

9. Task Automation

• SQL Server Agent configuration
• Scheduled tasks, operators
• Automated task scripts and security

10. SQL Server Replication

• Replication architecture and definitions
• Merge, Snapshot, Transactional replication
• Publication & Subscription
• HTTP Merge structure

11. High Availability

• Log Shipping
• Database Mirroring
• SQL Server Clustering
• Peer-to-Peer Replication
• Always On Availability Groups

What You Will Gain at the End of Training

• Learn the installation, configuration, and updating processes of SQL Server 2019 through practical application.
• Full proficiency in database creation, management, migration and monitoring
• Ability to develop, test and implement backup and recovery strategies
• Understanding the SQL Server security model and effectively managing roles, users, and permissions
• Automating tasks and creating alert systems with SQL Server Agent
• Understanding replication and high availability solutions at the application level
• Advanced database management practice with real-world scenarios

Querying SQL Server 2019,

About Education

Querying SQL Server 2019,This is a practical training course designed for individuals who want to learn database query languages and write effective queries in the Microsoft SQL Server environment. Throughout the training, participants will become proficient in using SQL Server Management Studio (SSMS), writing basic and advanced T-SQL queries, data grouping, multi-table queries (JOIN), data sorting and filtering.

The training is conducted using examples supported by real-world scenarios and aims to improve participants' query writing skills in SQL Server.

Prerequisites

• Basic knowledge of computer and office software
• No prior knowledge of SQL or databases is required.
• Familiarity with working with data and basic algorithm logic is beneficial.
• Those who have previously used Excel, data analysis or reporting tools may adapt more quickly.

Duration of Training

Toplam Süre: 5 Gün (Günde 6 saat)
Toplam Eğitim Saati: 30 saat
Eğitim Formatı: Uygulamalı ve interaktif yüz yüze/online ortam

Who Should Participate?

• Data analysts, reporting specialists, and BI developers who want to learn SQL
• Software developers who want to acquire basic data querying skills
• System administrators and technical team members working with SQL Server
• All professionals who work with data but want to strengthen their technical infrastructure
• University students, those who want to start their career in a data-driven field

Educational Content

Introduction and Basic Concepts

• What are data, databases and DBMS?
• Relational database structure and table logic
• SQL language and areas of use
• Introduction to SQL Server and SSMS interface
• Query execution methods

Quick Start to T-SQL

• What can be done with SQL?
• Basic T-SQL components and command classification
• Retrieving data with the SELECT command
• Listing tables and columns

Data Query with SELECT

• Simple SELECT queries
• DISTINCT and SELECT COUNT (DISTINCT)
• Column and table aliases

Operators and Filtering

• Arithmetic operators
• Comparison and logical operators with WHERE condition
• AND – OR, IN, LIKE, BETWEEN, IS NULL
• Wildcards in the LIKE operator

Sorting and Result Limitation

• ORDER BY
• OFFSET – FETCH
• TOP command usage

Grouping and Working with Grouped Data

• Aggregation functions: SUM, COUNT, MIN, MAX, AVG
• DISTINCT ile aggregate fonksiyonlar
• Using GROUP BY and HAVING
• Difference between HAVING and WHERE
• GROUPING SETS, CUBE ve ROLLUP
• SQL query processing order

Query with Multiple Tables (JOIN)

• Database schema and table relationships
• Primary key (PK) and foreign key (FK)
• JOIN types and usage logic
  • INNER JOIN
  • LEFT / RIGHT JOIN
  • FULL JOIN
  • CROSS JOIN
  • SELF JOIN and advanced JOIN structures

SET Operators and PIVOT Operations

• UNION and UNION ALL
• EXCEPT and INTERSECT
• Data transformation operations with PIVOT and UNPIVOT

What You Will Gain at the End of Training

• Ability to write queries confidently in an SQL Server environment
• Proficiency in basic and intermediate T-SQL commands
• Practical experience that meets real-life data query needs
• Ability to apply JOINs, grouping, filtering and data sorting techniques
• Ability to work with PIVOT and other advanced query techniques
• Strong foundation in data analysis, reporting, BI, and software development

Basic Python Training

About Education

Basic Python Training, programlamaya giriş yapmak isteyen katılımcılar için Python dili üzerinden sistematik ve uygulamalı bir başlangıç sunar. Eğitim, yazılım mantığını öğrenmek isteyen yeni başlayanlardan, veri analizi, yapay zekâ ve otomasyon projelerinde Python’a ihtiyaç duyan teknik profesyonellere kadar geniş bir katılımcı kitlesine hitap eder.

Katılımcılar; değişkenler, veri tipleri, kontrol yapıları, fonksiyonlar, nesne yönelimli programlama, dosya işlemleri ve veritabanı bağlantısı gibi konuları adım adım öğrenecek, eğitim sonunda orta seviye Python projelerini tek başına geliştirebilecek bilgi ve yetkinliğe ulaşacaktır.

Prerequisites

• Programlama bilgisi
• Temel bilgisayar kullanımı ve algoritma mantığına ilgi duymak yeterlidir.
• Kodlama disiplinine açık olmak ve düzenli pratik yapmak öğrenme sürecini hızlandırır.

Duration of Training

Toplam Süre: 5 Gün (Günde 6 saat)
Toplam Eğitim Saati: 30 saat
Eğitim Formatı: Uygulamalı ve interaktif yüz yüze /online ortam

Who Should Participate?

• Programlama dünyasına giriş yapmak isteyen herkes
• Yazılım geliştirme temellerini Python üzerinden öğrenmek isteyen öğrenciler
• Veri bilimi, yapay zekâ ve makine öğrenmesi gibi alanlara yönelmek isteyenler
• Test, otomasyon, veritabanı işlemleri gibi alanlarda Python kullanmak isteyen teknik personel
• Python diline ihtiyaç duyan tüm mühendislik, istatistik veya iş analitiği profesyonelleri

Educational Content

• Python Giriş
  • Python programlama dilini tanıma
  • Python ve IDE Kurulumu
  • Output işlemleri
• Data Types – Veri Türleri ve Bilgisayarın Çalışma Mantığı
  • NoneType ve Numeric (Sayısal) Veri Tipleri
  • Dizi Halindeki Veri Tipleri
  • Listeler (List)
  • Demetler (Tuple)
  • Setler (Set)
  • Sözlükler (Dictionary)
• Operators – Operatörler
  • Arithmetic Operators (Aritmetik Operatörler)
  • Assignment Operators (Atama operatörleri)
  • Comparison Operators (Karşılaştırma operatörleri)
  • Logical Operators (Mantıksal operatörler)
  • Operatörlerde KISA DEVRE (Associativity (Birleşme Özelliği))
  • Unary Operators (Tek terimli operatör)
  • Identity Operators (Benzerlik Operatörleri)
  • Bitwise Operators (Bitsel operatörler)
  • Membership Operators (Üyelik Operatörleri)
  • Ternary Conditional Operators – Üçlü Karşılaştırma Operatörleri
  • Number System Conversion (Sayı Sistemi Dönüşümü)
• Math Modülü – Veri Alma işlemleri – DEBUG
  • Math modülü incelemesi
  • Input işlemleri
  • Hata ayıklama
• Flow Control – Akış Kontrolü
  • If Clauses – If deyimi
  • Nested If Clauses – İç içe If deyimi
  • For Loop – For döngüsü
  • While Loop – While döngüsü
  • Break, Continue, Pass Statements – Break, Continue, Pass İfadeleri
  • Range Function – Range İfadesi
  • ASCII T
• Functions – Fonksiyonlar
  • Fonksiyonlara Giriş
  • Dönüş değeri olmayan parametresiz (argümansız) fonksiyonlar
  • Dönüş değeri olmayan parametreli (argümanlı) fonksiyonlar
  • Dönüş değeri olan parametresiz (argümansız) fonksiyonlar
  • Dönüş değeri olan parametreli (argümanlı fonksiyonlar
  • Birden fazla dönüş değeri olan fonksiyonlar ve paketten çıkarma işlemi
  • Pass by value (değer geçişi) – Pass by reference (adres geçişi)
  • Types of Arguments (Argümanların tipleri)
  • Variable-Length Arguments (Sınırsız sayıda değer alma işlemleri)
  • Local Variable (Yerel değişken) vs Global Variable (Global değişken)
  • Recursive ve Iterative Fonksiyonlar
  • Lambda Anonymous Function (İsmi olmayan fonksiyon)
  • Özel Fonksiyonlar (map, filter, reduce, zip, enumerate, all, any fonksiyonu)
  • Decorators (Dekoratörler diğer bir adıyla Süsleyiciler)
• Modules – Modüller
  • Modüllerle Çalışma
  • Kendi modülümüzü oluşturma ve kullanma
  • Special Variable (Özel değişken) olan namedeğişkeninin işlevi

• Object Oriented Programming – Nesneye Yönelik Programlama
  • Built-in Types (Tanımlı Tipler) (Python’da varsayılan veri tipleri)
  • Fonksiyon objeleriyle çalışma
  • Kendi class’ımızı (sınıfımızı – veri tipimizi) oluşturma
  • Special Variables ve Special Methods (Özel değişkenler ve metotlar)
  • Class kullanılarak oluşturulan objelerin özelliklerinin özelleştiri
  • Objelerin bilgilerinin güncellenmesi ve karşılaştırılması
  • Instance vs Class (Static) Variables
  • Instance vs Class vs Static Methods
  • Inner Class (class içinde class)
  • Inheritence (Kalıtım)
  • MRO – Method Resolution Order
  • Constructor
  • Polymorphism (Çok biçimlilik)
  • Duck Typing (Ördek Yazımı)
  • Operator Overloading (Operatörün aşırı yüklenmesi)
  • Magic Methods (Büyülü Metotlar)
  • Method Overloading (Metotun aşırı yüklenmesi)
  • Method Overriding (Metotun geçersiz kılınması)
  • Abstract Classes (Soyut Sınıflar) ve Abstract Methods (Soyut Metotlar)

• Iterators – Generators
  • Iterators(İteratörler – Yineleyici) Kavramı
  • Generators (Üreteçler)
  • Kendi fonksiyonumuzu modüle ekleme

• Exception Handling
  • Exception Handling (İstisnayı idare etme)
  • Exception bilgisi görüntüleme ve finally anahtar kelimesi
  • Multi Exception Handling (Çoklu Olağandışılığı İdare Etme)
  • Programımıza aykırı durumları Handle Etme (Logical Error)
  • Duruma göre kendi Exception’ımızı (olağandışılığımızı) fırlatma
• Dosya İşlemleri
  • Dosya oluşturma ve yazma işlemleri
  • Dosya okuma işlemleri
  • Dosyalarda kullanılan fonksiyonlar
  • Dosyalarda değişiklik yapma
• SQLite Veritabanı
  • SQLite Veri tabanı ve tablo oluşturma
  • Tablolara veri ekleme
  • Tablodaki verileri çekme
  • Tablodaki verileri silme ve güncelleme

What You Will Gain at the End of Training

• Python programlama dilinde yetkinlik kazanma
• Temel algoritmalar ve kontrol yapıları kurma becerisi
• Fonksiyonel ve nesne yönelimli programlama pratiği
• Hata yönetimi, dosya işlemleri ve veritabanı bağlantısı kurabilme
• Veri işleme, otomasyon ve analiz gibi ileri konulara sağlam bir temel
• Kendi başına projeler geliştirebilecek teknik özgüven

Designing and Implementing a Microsoft Azure AI Solution (AI-102T00

About Education

Designing and Implementing a Microsoft Azure AI Solution (AI-102T00) training course aims to equip software developers with the skills to plan, design, develop, deploy, and manage Azure AI services by taking on the role of Artificial Intelligence Engineer.
This training course will demonstrate the use of services such as Azure Cognitive Services, Azure Cognitive Search, and Azure OpenAI. Real-world scenarios will be addressed using REST APIs and SDKs in C# or Python.

Prerequisites

• Software development knowledge (experience working with at least one of the C# or Python languages)
• Knowledge of Azure fundamentals (Azure portal usage, resource creation, basic service logic)
• Experience working with REST APIs (JSON, HTTP requests, authentication processes)
• Familiarity with basic data processing and artificial intelligence concepts (entry-level knowledge in areas such as machine learning, NLP, and visual processing)
• People with general cloud and software development experience can participate in this training, even if they have not worked with Azure AI services before.

Duration of Training

Toplam Süre: 4 Gün (Günde 6 saat)
Toplam Eğitim Saati: 24 saat
Eğitim Formatı: Uygulamalı ve interaktif yüz yüze /online ortam

Who Should Participate?

• Software developers who want to develop real applications using Azure AI services
• AI engineer candidates who want to plan, manage, and deploy projects involving artificial intelligence.
• Azure portal, people who know C# or Python, and have worked with REST/JSON.
• Professionals who want to develop products in areas such as bots, smart search, and visual/audio/speech analysis.

Educational Content

1. Planning and Preparation

• Azure AI services overview, architectural design, and responsible AI principles

2. Creating & Consuming Cognitive Services

• Source creation, endpoint/key management, REST API and SDK usage.

3. Security & Surveillance

• Identity verification, network security, cost/performance/telemetry monitoring, deployment to container environment

4. Computer Vision

• Visual analysis, classification, object recognition, face recognition, OCR, video analysis.

5. Natural Language Processing

• Language recognition, sentiment analysis, entity recognition, translation, question-answering, speech-to-text and vice versa.

6. Cognitive Search

• Smart search, enrichment, knowledge store, semantic and vector search with Azure AI Search

7. Document Intelligence

• Automatic data extraction from forms and documents, pre-trained & custom models.

8. Generative AI & OpenAI

• Natural language, code, image generation, and RAG-based solutions with Azure OpenAI integration.

What You Will Gain at the End of Training

• Analysing Azure AI solutions to select the right services, plan and configure them securely.
• Transforming various AI scenarios into applications with Cognitive Services
• Developing end-to-end solutions in the fields of visual, language, speech, document, search, and generative AI.
• Deploying solutions in containers, monitoring, ensuring security, and optimising costs.
• Prepare for the AI-102 exam and reach the level required to apply for the Azure AI Engineer Associate certification.

Application Development Training with Claude

About Education

This training is designed for developers, product managers, and tech enthusiasts who want to add a new dimension to application development processes using Anthropic's powerful artificial intelligence model, Claude. Throughout the training, Claude's API capabilities, natural language processing (NLP), data analysis, content creation, automation, and artificial intelligence-powered application scenarios will be covered in detail. Participants will gain hands-on knowledge on topics such as how to develop interactive applications with Claude, how to process user inputs, and how to interpret Claude's outputs.

Prerequisites

• Basic knowledge of software development (Python, JavaScript or similar language preferred)
• Basic information about API usage
• General familiarity with artificial intelligence and machine learning concepts (preferred but not required)

Duration of Training

Toplam Süre: 3 Gün (Günde 6 saat)
Toplam Eğitim Saati: 18 saat
Eğitim Formatı: Uygulamalı ve interaktif yüz yüze /online ortam

Who Should Participate?

• Application developers and software engineers
• Product managers and digital transformation professionals
• Entrepreneurs who want to integrate AI solutions into their products

Educational Content

Day 1 – Fundamentals and Getting Started

Morning – Claude Introduction

• Overview of Claude models (Opus 4, Sonnet 4)
• Choosing the right model: balancing performance and cost

Before Lunch – API Basics

• Obtaining an API key and authorisation
• Messages API structure and message flow
• Practical: Sample application with Python/Node

Afternoon – Prompt Engineering

• Prompt techniques for Claude 4
• Examples of information extraction and structuring
• Application: prompt design that produces structured output

Day 2 – APIs, Tools and Multimodality

Morning – Advanced API Usage

• Message Batching (Message Batches API)
• Prompt caching and performance
• Code example: adding a caching layer

Before Lunch – File & PDF Analysis

• File upload and analysis
• PDF content processing

Afternoon – Vehicle Usage & Agents

• Claude's driving characteristics
• Developing a JSON-based task agent
• Mini agent application: resume parser

Day 3 – Advanced Architecture and Implementation

Morning – Model Context Protocol (MCP)

• What is MCP and what does it do?
• Use with backend integration

Before Lunch – Visual Skills

• Visual data processing, graph/chart interpretation
• Application: extracting structured data from images

Afternoon – Agent Systems & Evaluation

• Smart agents with multi-step planning
• Evaluation criteria and automation
• Project: End-to-end Claude-supported workflow

Additional Module – RAG (Retrieval-Augmented Generation)

• Using Claude with external information sources
• LlamaIndex or database integration
• Setting up a question-and-answer system

What You Will Gain at the End of Training

• Effective use of the Claude API
• Advanced prompt design
• Multimodal and tool-agent systems
• Artificial intelligence evaluation and production readiness

Collaboration Automation (CLAUTO)

About Education

Prerequisites

CLCOR certification or knowledge, CCNA certification or knowledge

Duration of Training

Toplam Süre: 5 Gün (Günde 6 saat)
Toplam Eğitim Saati: 30 saat
Eğitim Formatı: Uygulamalı ve interaktif yüz yüze /online ortam

Who Should Participate?

• Collaboration Administrators
• Devnet specialists

Educational Content

Section 1: Introduction to Cisco Collaboration and Automation

               – Overview of Cisco collaboration tools (Cisco Unified Communications Manager, Webex, etc.)

               – Introduction to automation and its benefits in Cisco collaboration

               – Exploring common collaboration tasks that can be automated

Section 2: Python Basics for Automation

               – Introduction to Python programming language

               – Setting up Python environment (IDE, libraries, etc.)

               – Basic Python syntax and data types

               – Loops in Python

               – Define function in Python

Section 3: GIT and GitHUB/GitLAB

               – Introduction of Git

               – Git Usage and feature

               – GitHub/GitLab and its usage

Section 4: Working with Cisco Collaboration APIs

               – Introduction to Cisco Collaboration APIs (RESTful APIs, AXL, etc.)

               – Understanding API documentation and authentication

               – Making API requests using Python (requests library)

Section 5: Automating Call Management and Daily Task

               – Automating call routing and forwarding

               – Automating voice gateway

               – Automating user provisioning and account management

               – Modifying settings and configurations using APIs

               – Bulk operations and automating repetitive tasks

               – Retrieving call logs and call history data

Section 6: Monitoring and Analytics Automation

               – Retrieving and analyzing collaboration data (usage, performance, etc.)

               – Generating reports and dashboards using Python libraries

               – Proactive monitoring and alerting for collaboration systems

Q&A and open discussion

What You Will Gain at the End of Training

• git (version kontrol)
• postman
• python knowledge and  python libraries usage
• rest api usage
• automation scripting of cucm and vg