Generative AI Eğitimi

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• Why Python is popular on many areas?
• Big Data and Database Management
• Data Science and Analysis
• Machine Learning (ML:
• Artificial Intelligence (AI:
• Network Programming and System Automation 

• The Python Standard Library
• Built-in Functions and Modules
• Basic Operators and Type Casting
• Numeric Data Types and Functions
• String Data Type and Functions

• if-else
• For loop
• While loop
• break and continue statements

• Function Definition
• Scope Rules
• Recursion
• Random Module Functions 

• Immutable vs Mutable Types
• List and Tuple Functions
• Comparison
• Conversion
• Multi-dimensional Lists and Tuples 

• Key and Value Pairs
• Dictionary Functions
• Sorting and Converting 

• Important Libraries
• How to Install and Import
• Examples

• Open a File with r/w/a/b Modes
• File Operations
• File and Directory Methods

• Exception Types
• Multiple Exceptions
• try and except block
• Finally expression 

• Module 1: List Comprehension Lab
• Module 2: What is Model Driven Automation
• Module 3: What is HTTP?
• Module 4: How HTTP works?
• Module 5: What is Rest API
• Module 6: What are API Data Formats?
• Module 7: List Comprehension
• Module 8: Parsing Public Colorado Population API With Python Lab
• Module 9: Parsing News API With Python Lab
• Module 10: Parsing NASA API With Python Lab
• Module 11: Parsing Finance APIs With Python Lab
• Module 12: Parsing Capital Cities JSON With Python Lab
• Module 13: Parsing Star War JSON With Python Lab
• Module 14: Parsing Game Of Thrones JSON With Python Lab
• Module 15: Creating Custom API: Open Weather
• Module 16: Webex API Chat Bot With Web Hook Lab
• Module 17: Wolfram Alpha API
• Module 18: Webex API Chat Bot With Wolfram Alpha API
• Module 19: ChatterBot
• Module 20: Webex API With ChatterBot 

• Module 1: What is Data Science?
• Module 2: What is Artificial Intelligence?
• Module 3: The Relation Between Artificial Intelligence, Data Science, Machine Learning and Deep Learnig
• Module 4: What Data Scientist Do?
• Module 5: Creating Data Frame From API and HTML With Pandas Lab
• Module 6: Creating Data Frame From Python Data Types With Pandas Lab
• Module 7: Creating Data Frames from JSON With Pandas Lab
• Module 8: Creating Data Frame From TXT With Pandas Lab
• Module 9: Sorting Values At Data Frames With Pandas Lab
• Module 10: Create Excel With Openpyxl With Pandas Lab
• Module 11: Creating Data Frame From Excel and Clipboard With Pandas Lab
• Module 12 Creating Data Frames From CSV With Skip Rows Functions At Pandas Lab
• Module 13: Salaries Dataset Part 1 Set Index, Drop, NA Values Functions at Pandas Lab
• Module 14: Salaries Dataset Part 2 Making Querries With Pandas Lab
• Module 15: Salaries Dataset Part 3 Making Multiple Querries-Locate With Pandas Lab
• Bonus Module: Rename & Replace DataFrames
• Module 16: Pandas DataFrame Append, Concat, Transpose Lab
• Module 17: Pandas Nunique Lab
• Module 18: Copy Sheet-Delete Row & Columns at Excel With Openpyxl Lab
• Module 19: Seperate & Save Sheets As New WorkBooks at Excel With Xlwing Lab
• Module 20: Merge & Seperate Workbooks into New Workbooks at Excel With Openpyxl Lab
• Module 21: Heart Attack Analysis Part 1 Intro
• Module 22: Heart Attack Analysis Part 2 Value Counts With Pandas Lab
• Module 23: Heart Attack Analysis Part 3 Features (Value Count & Nunique: With Pandas Lab
• Module 24: Heart Attack Analysis Part 4 Group By With Pandas Lab
• Module 25: Heart Attack Analysis Part 5 Cut with Pandas Lab
• Module 26: Video IMDB Top 250 HTML Parsing Lab With Pandas and Beautiful Soup Lab
• Module 27: Lambda Lab
• Module 28: Numpy Intro
• Module 29: Mean, Variance, Sigma Lab
• Module 30: Median Lab
• Module 31: Matplotlib 1 Data Visualization Lab
• Module 32: Matplotlib 2 Subplots Lab
• Module 33: Matplotlib 3 Subplots Pie Lab
• Module 34: Matplotlib 4 Spanish Footbal Federation Lab
• Module 35: Matplotlib 5 With Pandas Data Reader Lab
• Module 36: Matplotlib 6 Customize Time Series Tata Global Lab
• Module 37: Matplotlib 7 Customize Time Series Colorado Lab (rotation, indent, time format)
• Module 38: Matplotlib 9 Random Walk Probability Lab
• Module 39: Matplotlib 10 Random Multiple Walk Probability Lab
• Module 40: Matplotlib 11 Birthday Probability Lab
• Module 41: Matplotlib 12 Birthday Probability %50 Annotate Lab
• Module 42: Matplotlib Bonus Scatter Lab
• Module 43: Matplotlib Annotate & Arrowprops Lab
• Bonus Lab 1: Advanced 3D Visualization With Matplotlib
• Bonus Lab 2: Data Visualization With PyGoogleChart
• Bonus Lab 3: Data Visualization With Plotly
• Bonus Lab 4: Data Visualization With Dash
• Module 44: Seaborn Lineplot Lab
• Module 45: Advertisement Dataset Seaborn Scatterplot, Heatmap, Pairplot Lab
• Module 46: Heart Attack Analysis Part 6 Seaborn Barplot Lab
• Module 47: Heart Attack Analysis Part 7 Seaborn Catplot Lab
• Module 48: Heart Attack Analysis Part 8 Seaborn Boxplot Lab
• Module 49: Log File Management With Python Lab
• Module 50: Object Oriented Programing Encapsulation
• Module 51: Object Oriented Programing Inheritance
• Module 52: Parsing Star Wars Episode 3 Scenario Lab
• Module 53: Regular Expressions Parsing Words.txt file Lab
• Module 54: Regular Expressions Kill Bill Phrase With regex101 Lab
• Module 55: Regular Expressions Parsing Emails Lab
• Module 56: Regular Expressions Split, Substitude, Findall Lab
• Module 57: Socket Programming Part 1 Sending & Receiving Data Lab
• Module 59: Socket Programming Part 2 Parsing Binary Data Lab
• Bonus Lab: Multi-Threading With Socker Programming
• Module 60: SQlite3 Introduction To SQlite3 Database Company Lab
• Module 61: SQLite3 Harvard Movies Project Lab
• Module 62: Netflix Dataset
• Module 63: Spotify Dataset 

• Module 1: What is Machine Learning
• Module 2: Machine Learning Methods
• Module 3: Supervised Machine Learning Regression Introduction
• Module 4: Advertisement Dataset Multiple Linear Regression
• Module 5: Advertisement Dataset Polynomial Regression
• Module 6: How to Save Data Model and Load
• Module 7: Supervised Machine Learning Classification
• Module 8: Using Standard Scaler Method For Scattered Distributed Data: Breast Cancer Dataset
• Module 9: Label Encoder: Titanic Dataset
• Module 10: Cross Validation
• Module 11: Lasso
• Module 12: KNN
• Module 13: Unsupervised Machine Learning Models 

• Module 1: Introduction To Deep Learning
• Module 2: What is Neural Network?
• Module 3: What is Deep Nerural Network?
• Module 4: How to Design Deep Neural Network?
• Module 5: Multi Layer Perceptron:
• Module 6: Breast Cancer Dataset Prediction With MLP
• Module 7: Artificial Neural Networks
• Module 8: Desigining Deep Neural Network Tensorflow Play Ground
• Module 9: Digit Detection With Artificial Neural Networks: Mnist Dataset
• Module 10: Pima Indians Diabetics DataSet Simple Classification with ANN
• Module 11: Breast Cancer Dataset Prediction With ANN
• Module 12: Boston Houses Dataset Prediction With ANN
• Module 13: One Hot Encoder: Iris Flower Dataset Multiple Classification With ANN
• Module 14: Early Stop Callback
• Module 15: Multiple Early Stop CallBacks
• Module 16: Heart Attack Prediction With ANN & Multiple Early Stop CallBacks
• Module 17: Convolutional Neural Networks
• Module 18: Image Processing With Python
• Module 19: Data Preprocessing & Data Modelling For Image Processing
• Module 20: Digit Detection With Convolutional Neural Networks: Mnist Dataset
• Module 21: Multiple Digit Detection With Convolutional Neural Networks
• Module 22: Object Detection With Python
• Module 23: Face Recognition With Python
• Module 24: Pneumonia Prediction From X-Ray With Convolutional Neural Networks
• Module 25: Lung Cancer Prediction From X-Ray With Convolutional Neural Networks
• Module 26: Recurrent Neural Networks
• Module 27: Stock Prediction With Long Short Term Recurrent Neural Networks
• Bonus Lab: Natural Language Processing & Multiple Text Classification With Long Short Term Recurrent Neural Networks
• Module 28: Creating Images from Text With Generative Adversarial Networks
• Module 29: Generating Python Codes from Text With Transformer Model
• Module 30: Generating Texts & Articles from Text With Transformer Model 

• Module 1: Email With Python Part 1 smtplib & email.message Lab
• Module 2: Email With Python Part 2 Yagmail Lab
• Module 3: Email With Python Part 3 Attached Email with Email.Message Lab
• Module 4: Email With Python Part 4 Time Scheduled Mail Lab
• Module 5: Email With Python Part 5 Bitcoin Api Auto Alarm Management With Email Lab
• Module 6: Email With Python Part 6 Email With Excel Lab
• Module 7: Email With Python Part 7 Sending attached file as html in email Lab
• Module 8: Email With Python Part 8 Sending Email within VPN Lab
• Module 9: Creating Widget With Tkinter Lab
• Module 10: Restaurant Menu With Tkinter Lab
• Module 11: Text To Speech With gTTS Lab
• Module 12: Text To Speech With Pyttsx Lab
• Module 13: Speech to text gTTS Lab
• Module 14: Speech To Text Pyttsx3 Lab
• Module 15: Making Google Searches With Python
• Module 16: Making Wikipedia Searches With Python
• Module 17: Making Youtube Searches With Python
• Module 18: Pyaztro: Getting Horoscopes Data via Python
• Module 19: Pytesseract
• Module 20: Weather Forecast Application With Tkinter, SQL, Text To Speech, Speech To Text
• Module 21: Weather Forecast Application With Tkinter, JSON, Text To Speech, Speech To Text
• Module 22: Making Mp3 Player Application With Tkinter
• Module 23: Managing Charts With Tkinter
• Module 24: Managing Hyperlinked URLs With Tkinter
• Module 25: Making Newspaper Dashboard Application With Tkinter
• Module 26: Making Multi Digit Detection Application With CNN and Tkinter.
• Module 27: Introduction to Flask: Server Working
• Module 28: Flask-RESTX Get/POST/PUT/DELETE Requests With Parameters & Swagger
• Module 29: Making Calculator With Flask
• Module 30: Making Phone Book With Flask
• Module 31: Introduction to Fast API
• Module 32: Create Your Own API With FAST API: Get, Post, Put, Delete
• Module 33: Making Applications With Fast API
• Module 34: Making Weather Forecast Application With Fast API
• Module 35: Making Machine Learning Application With Fast API
• Module 36: Making Deep Learning Application With Fast API
• Module 37: Display Images at Back End Fast API Swagger as Response Body
• Module 38: Display Images at Front End Fast API Web Browser
• Module 39: Display Hyperlinked URLs at Front End Fast API Web Browser
• Module 40: Flask & Fast API: Project Wolfram Alpha API Chatbot Project
• Module 41: Creating Cluster Services via Fast API 

• Module 1: Creating AI Chatbot With NLP and Sentiment Analysis by English
• Module 2: Creating AI Chatbot With NLP and Sentiment Analysis by English via Tkinter
• Module 3: Creating AI Chatbot With NLP and Sentiment Analysis by English via Tkinter & Text To Speech, Speech to Text
• Module 4: Creating Transformer Based AI API in English & Turkish via Fast API
• Module 5: Integrating News Services Into Transformer Based AI API
• Module 6: Integrating Weather Forecast Services Into Transformer Based AI API
• Module 7: Integrating Date & Time Services Into Transformer Based AI API
• Module 8: Integrating Financial Services Into Transformer Based AI API
• Module 9: Integrating Stock Market Services Into Transformer Based AI API
• Module 10: Integrating Stock Market Analysis Chart Services Into Transformer Based AI API
• Module 11: Integrating Stock Market Prediction Chart Services Into Transformer Based AI API
• Module 12: Integrating History Services Into Transformer Based AI API
• Module 13: Integrating Geography Services Into Transformer Based AI API
• Module 14: Integrating Mathematics Services Into Transformer Based AI API
• Module 15: Integrating Database Management Services Into Transformer Based AI API
• Module 16: Integrating Text to Image Services Into Transformer Based AI API
• Module 17: Integrating Text Generation Services Into Transformer Based AI API
• Module 18: Integrating Code Generation Services Into Transformer Based AI API