Eğitim Adı: Applied AIOps Bootcamp

Eğitim Süresi: 16 Gün / 128 Saat / Cumartesi Günleri + 10 Online Video Ders

Tarihler: 25.01.2024-10.05.2025

Eğitim Şekli: Canlı Online Ders

Eğitimin Amacı: Eğitimin amacı, geleneksel ve üretken yapay zeka tekniklerini derinlemesine öğrenerek, pratik uygulamalı projeler aracılığıyla bu teknolojilerin geliştirilmesi, etkin kullanımı ve yenilikçi yapay zeka uygulamalarının hayata geçirilmesi konularında katılımcılara yetkinlik kazandırmaktır.

Eğitimimiz ücretlidir. Lütfen fiyat bilgisi almak için en alt kısımda yer alan formu doldurun.

Online Canlı Eğitim İçeriği

Part 1: Python

Module 1: Language Overview

Module 2: Standard Data Types

Module 3: Flow Control

Module 4: Functions

Module 5: Lists and Tuples

Module 6: Dictionaries

Module 7: External Libraries

Module 8: Basic File Operations

Module 9: Exception Handling

Module 10: OS Operations & File Management

Module 11: Advanced Algorithms

Module 12: Log File Index Management

Module 13: Python Code Index Management At Any Folder

Module 14: Object Oriented Programming: Encapsulation & Inheritance

Part 2: REST API With Python

Module 1: What is Model Driven Automation

Module 2: What is HTTP ?

Module 3: How HTTP works ?

Module 4: What is Rest API

Module 5: What are API Data Formats?

Module 6: List Comprehension

Module 7: Parsing JSON With Postman

Module 8: Parsing Capital Cities JSON With Python 

Module 9: Parsing Star War JSON With Python 

Module 10: Parsing Game Of Thrones JSON With Python 

Module 11: Parsing Public Colorado Population API With Python 

Module 12: Parsing News API With Python 

Module 13: Parsing NASA API With Python 

Module 14: Working With Open AI API

Module 15: Parsing API With Postman

Module 16: Parsing Forex API & Bitcoin API With Python

Part 3: Data Science

Module 1: What is AI, Data Science, Machine Learning, Deep Learning

Module 2: Creating Data Frames From JSON, Python Data Types, Excel, CSV

Module 3: Working With Numpy

Module 4: Managing Data Frames With Pandas and Numpy

Module 5: Data Frame Append, Concat, Transpose

Module 6: Pandas Values, value_counts, unique, nunique 

Module 7: Sorting Data With Multiple Queries at Data Frames IMKB Stock Market

Module 8: Pandas Group By

Module 9: Analyzing Big Data With Python 

Module 10: Intro to Matplotlib(plot, scatter, bar)

Module 11: Matplotlib Subplots & Pie

Module 12: Matplotlib With Yfinance For Stock Market Visualization

Module 13: Customize Time Series Colorado Lab (rotation, indent, time format)

Module 14: Matplotlib Annotate & Arrowprops

Module 15: Advanced 3D Visualization With Matplotlib

Module 16: Data Visualization With Plotly

Module 17: Plotly With Size & Trendline Ordinary Least Squares Regression

Module 18: Data Visualization With Seaborn 

Module 19: Data Analysis Heart Attack 

Module 20: Data Analysis Covid19

Module 21: Data Analysis Iphone Sales

Module 22: Project Data Analysis NYC Service Requests

Module 23: Project Data Analysis Netflix

Module 24: Project Data Analysis AAL Sales Analysis

Module 25: Data Analysis GDP(Gross Domestic Product)

Module 26: Data Analysis Financial Risk Analysis Of Mutual Funds Investments.

Module 27: Data Analysis Turkish Stock Market With Technical Indicators(SMA20,EMA20,RSI,MACD,HMA)

Module 28: Data Analysis Investment Portfolio Management

Part 5: Machine Learning With Python

Module 1: What is Machine Learning

Module 2: Machine Learning Methods

Module 3: Supervised Machine Learning Linear Regression

Module 4: Supervised Machine Learning Polynomial Regression  

Module 5: Multiple Linear Regression

Module 6: Multiple Polynomial Regression

Module 7: How to Save Data Model and Load

Module 8: Stock Market Prediction With Linear Regression

Module 9: Standard Scaler

Module 10: Lasso 

Module 11: Cross Validation & Pipeline

Module 12: Supervised Machine Learning Classification

Module 13: Label Encoder & Logistic Regression: Titanic

Module 14: Advanced Momentum Trading Strategies Via Candlestick Formations With RandomForestClassifier

Module 15: Multiple Text Classification With Machine Learning

Module 16: RFM Analysis/Hierarchical Clustering/Customer Segmentation

Module 17: Multi Layer Perceptron

Part 6: Deep Learning With Python

Module 1: Introduction To Deep Neural Networks

Module 2: How to Design Deep Neural Networks

Module 3: House Price Prediction With Artificial Neural Networks & Early Stop Callback

Module 4: One Hot Encoder & Multiple Classification With Artificial Neural Networks

Module 5: Heart Attack Prediction With Artificial Neural Networks& Multiple Early Stop Callbacks

Module 6: Intent Classification Assistant Chatbot With Artificial Neural Networks & Natural Language Processing 

Module 7: Convolutional Neural Networks

Module 8: Digit Detection With Artificial Neural Networks: Mnist Dataset

Module 9: Data Preprocessing & Data Modelling For Image Processing

Module 10: Object Detection With Python

Module 11: Recurrent Neural Networks and LSTM

Module 12: Stock Market Prediction With Recurrent Neural Networks and LSTM

Module 13: Financial Anomaly Detection With Prophet

Module 14: Stock Market Prediction With Prophet

Module 12: Network Anomaly Detection With Recurrent Neural Networks and LSTM

Module 13: Spam Email Classifier Recurrent Neural Networks and LSTM

Module 14: Deep Reinforcement Learning Stock Market Management

Part 7: Generative AI:

Module 1: What is Generative AI?

Module 2: The differences Of Generative AI From Traditional AI

Module 3: Semantic Similarity

Module 4: Sentimental Classification (Positive, Negative, Neutral)

Module 5: Summarization of Text 

Module 6: Intent-Classification

Module 7: Summarization of Generated Code

Module 8: Text-Generation

Module 9: Auto-Encoders

Module 10: Credit Card Fraud Detection with Autoencoders

Module 11: Working With Large Language Model LLama 3.3 through Ollama

Module 12: Document-Based Question Answering With Ollama, LLama3.3, Qdrant, Litserve and Gradio 

Module 13: Data Analysis With Ollama, LLama3.3 and flask-restx

Module 14: Transforming Vast Data into Actionable Insights with AI-Powered Business Intelligence via LLama3.3 and Streamlit 

Module 15: Finetune LLama3.3 With LoRa & Quantization 

Module 16: Working With Llama 3.3 Vision

Module 17: Finetune Llama 3.3 Vision with custom dataset

Bonus Online Video Eğitim İçeriği

Part 1: HTML Parsing With Python

Module 1: How HTML Parsing Works?

Module 2: HTML Parsing For imdb.html

Module 3: HTML Parsing For StackOverFlow

Module 4: HTML Parsing For GitHub

Part 2: RegEx With Python

Module 1: Parsing Star Wars Episode 3 Scenario

Module 2: Parsing Words.txt with RegEx

Module 3: RegEx search match group

Module 4: Parsing Emails With RegEx.

Part 3: Email With Python

Module 1: smtplib & email.message

Module 2: Yagmail

Module 3: Attached Email with Email.Message

Module 4: Time Scheduled Mail

Module 5: Bitcoin Api Auto Alarm Management With Email

Module 6: Email With Excel

Module 7: Sending attached file as html in email

Module 8: Sending Email within VPN

Part 4: Excel With Python

Module 1: Create Excel With Openpyxl

Module 2: Creating Data Frame From Excel

Module 3: Copy Sheet-Delete Row & Columns at Excel

Module 4: Seperate & Save Sheets As New WorkBooks at Excel

Module 5: Merge & Seperate Workbooks into New Workbooks at Excel

Module 6: Excel to TXT

Module 7: Receive Specific Data From Excel Sheets at Excel Workbook.  

Part 5: GUI Development With Tkinter 

Module 1: Creating Widget With Tkinter Lab

Module 2: Restaurant Menu With Tkinter Lab

Module 3: Weather Application With Tkinter, SQL & JSON

Module 4: Making Mp3 Player Application With Tkinter

Module 5: Managing Charts With Tkinter

Module 6: Managing Hyperlinked URLs With Tkinter

Module 7: Making Finance Dashboard Application With Tkinter

Module 8: Multiple Digit Detection App With Tkinter

Part 6: API Development With Flask-Restx 

Module 1: Introduction to Flask & How Web Server Works?

Module 2: API Development with Flask RestX

Module 3: API Endpoint & Query Parameters Management With Flask-RESTX Reqparse

Module 4: API Endpoint & Query Parameters With Multiple Choices by Flask-RESTX Reqparse

Module 5: Sql With Python CRUD(Create, Read, Update, Delete) 

Module 6: Parsing IMDB Sql Database With Python

Module 7: SQL & API Integration: Get/Post/Put/Patch/Delete

Module 8: Flask-RESTX Upload/Display/Download Photo

Module 9: Flask-RESTX Upload/Display/Download Excel

Module 10: Flask-RESTX Chatbot With OpenAI

Module 11: Flask-RESTX Chatbot With NewsAPI

Part 7: Linux

Module 1: Login: How to login and gather info about system

Module 2: History: Linux History and Distributions

Module 3: Basic Management Commands: alias, ls, cd, pwd

Module 4: BASH: Shell types: Bourne, Korn, Bash, Set Shell variables, env

Module 5: BASH: I/O Redirection: stdin, stdout, stderr, and sudo

Module 6: VI: Vi editor basic and advanced features

Module 7: Permissions

Module 8: Archiving: tar, gzip, bzip2, xz

Module 9: Installation: Linux operating system installation

Module 10: Filesystem Management

Module 11: Services: Management

Module 12: Account Management

Module 13: Process Management

Module 14: Software Management

Module 15: Log Management

Part 8: API Management With DevSecOps

Module 1: Implementing PostGreSQL

Module 2: PostGreSQL With Python

Module 3: Basic Authentication

Module 4: Device Management API With PostGreSQL, HTTPS & Basic Authentication

Module 5: Vault 

Module 6: Device Management API With PostGreSQL, HTTPS, Vault and Basic Authentication

Module 7: Device Management API With PostGreSQL, HTTPS, Vault and Json Web Token

Module 8: Device Management API With PostGreSQL, HTTPS, Vault, Json Web Token and LDAP Server

Module 9: Device Management API With PostGreSQL, HTTPS, Vault, Two Factor Authentication and LDAP Server

Part 9: Open AI API

Module 1: Text & Code Generation With Open AI API

Module 2: Generating Photo With Open AI API

Module 3: Ask Questions About Photo With Open AI API

Module 4: Change Current Photo Details With Open AI API

Module 5: Generating Video With Open AI API

Module 6: Ask Questions About Video With Open AI API

Module 7: Change Current Video Details With Open AI API

Module 8: Working With Webex API

Module 9: Webex API Integration With Open AI API

Module 10: Text To Speech & Speech To Text With Open AI API

Module 11: Data Analysis With Open AI API

Module 12: Chat With Your Documents via Open AI API and Gradio

Module 13: Transforming Vast Data into Actionable Insights with AI-Powered Business Intelligence via Open AI API and Streamlit

Module 14: Gradio User Login & Open AI API 

Module 15: Streamlit User Login & Open AI API

Module 16: Making AI Chatbot Application With Tkinter & Open AI API

Part 10: Docker

Module 1: Docker-Computing Evolution

Module 2: Docker-Software & Application Development-Waterfall versus Agile

Module 3: Docker-Software Test Types

Module 4: Docker-Construct A Python Unit Test Lab

Module 5: Docker-Introduction to DevOps

Module 6: Docker-Kubernetes Architecture

Module 7: Docker Architecture

Module 8: Docker on Linux Mac Windows

Module 9: How Docker Works

Module 10: Docker Host Installation On Centos v7.0

Module 11: NGINX Web Service Container Installation

Module 12: Interpret A Dockerfile

Module 13: Working With Container Images & Docker Hub

Module 14: Containerize Flask Web Service

Module 15: Containerize Flask Web Service With Virtual Environment

Module 16: Containerize An API

Module 17: Docker Cluster Services

Module 18: Container Network

Module 19: Volumes

Module 20: Containerize An Application Using Docker

Module 21: Docker-Compose

Module 22: Docker Swarm

Module 23: Containerize An AI Chatbot

Module 24: Load Balance An AI Application