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AI (KI) Development, KI Manager Weiterbildung V3


Content
  • Session 1 -Intro to the course and AI history and Applications in real life
  • Session 1 Part 1 - Introducing Course
  • Session 1 Part 2 - Introducing Programming
  • Session 1 Part 3 - Introducing Git & GitHub
  • Session 1 Part 4 - Introduction to AI
  • Session 1 Part 5 - Introduction to Social Entrepreneurship
  • 01-Part1.pdf
  • Session 2 - Introduction to Python and environment setup
  • Session 2 Part 1 - Re-Installation Git and GitHub
  • Session 2 Part 2 - Re-Installation
  • Session 2 Part 3 - Basic methodologies ( init, add)
  • Session 2 Part 4 - basic methodologies ( commit , statue , log)
  • Session 3 - Communication and soft skills
  • Session 3 Part 1
  • Session 3 Part 2
  • Session 3 Part 3
  • Session 3 Part 4
  • Session 4 - Python syntax, variables, and data types
  • Session 4 Part 1 - How to study programming
  • Session 4 Part 2 - Python history & future
  • Session 4 Part 3 - Install python
  • Session 4 Part 4 - Variables
  • 02-Part2.pdf
  • Py-01
  • Session 5 - Communication and soft skills
  • Session 5 Part 1 - Operators
  • Session 5 Part 2 - Operators
  • Session 5 Part 3 - Conditions
  • Py-02
  • Session 6 - Control flow: conditionals and loops
  • Session 6 Part 1 - Dict
  • Session 6 Part 2 - Set
  • Session 6 Part 3 - Tuple
  • Session 6 Part 4 - List
  • Py-03
  • Session 7 - Time management skills
  • Session 7 Part 1 - Data types part 2
  • Session 7 Part 2 - OOP intro
  • Session 7 Part 3 - OOP intro
  • Py-04
  • Session 8 - Functions and modules
  • 03- P3.pdf
  • Session 8 Part 1 - OOP part 2
  • Session 8 Part 2 - OOP part 2
  • Session 8 Part 3 - Inhertance
  • Session 8 Part 4 - Revision with projects part 1
  • Py-05
  • Session 9 -Time management skills
  • Py-06
  • Session 9 Part 1
  • Session 9 Part 2
  • Session 9 Part 3
  • Session 10 - Object-Oriented Programming basics
  • Session 10 Part 1
  • Session 10 Part 2
  • Session 10 Part 3
  • Session 10 Part 4
  • Py-01-sol.pdf
  • Py-02-sol.pdf
  • Py-03-sol.pdf
  • Py-04-sol.pdf
  • Py-05-sol.pdf
  • Py-06-Sol.pdf
  • Session 11 - Data structures: lists, tuples, dictionaries
  • Session 11 Part 1 - Python Recap
  • Session 11 Part 2 - Python Intermediate
  • Session 11 Part 3 - LinkedIn
  • Session 12 - Agile Methodes and practice
  • Py-07
  • Session 12 Part 1 - List comprehension
  • Session 12 Part 2 - Dict comprehension
  • Session 12 Part 3 - Functional programming
  • Session 12 Part 4 - Functional programming
  • Session 13 - Advanced data structures: sets, stacks, queues
  • Session 13 Part 1
  • Session 13 Part 2
  • Session 13 Part 3
  • Session 14 - Agile Methods and practice
  • Session 14 Part 1
  • Session 14 Part 2
  • Session 14 Part 3
  • Session 15 -Basic algorithms: sorting and searching
  • Session 15 Part 1 - Project covering
  • Session 15 Part 2 - OOP
  • Session 15 Part 3 - Functional Programming
  • Session 15 Part 4 - List and Dict comprehension
  • Session 16 - Problem-solving techniques
  • Session 16 Part 1 - Data Structure Intro
  • Session 16 Part 2 - Big O Notation
  • Session 16 Part 3 - String
  • Session 16 Part 4 - Array
  • Session 17 - Agile
  • Session 17 Part 1 - Array Part 2
  • Session 17 Part 2 - Array Part 2
  • Session 17 Part 3 - Linked List
  • Session 17 Part 4 - Linked List
  • 10-7-20204-p1.pdf
  • 10-7-20204-p2.pdf
  • Session 18 - Automation and working with external APIs
  • Session 18 Part 1 - File handling
  • Session 18 Part 2 - File handling
  • Session 18 Part 3 - Database intro
  • Session 18 Part 4 - Database
  • 11-7-2024.pdf
  • Session 19 - Agile
  • 12-7-2024.pdf
  • Session 19 Part 2
  • Session 19 Part 3
  • Session 19 Part 4
  • Session 20 -Probability basics
  • Session 20 Part 1 - Python Modules
  • Session 20 Part 2 - Time , OS
  • Session 20 Part 3 - Math , Requests
  • Session 20 Part 4 - System , Timeit
  • 15-7-2024.pdf
  • Session 20 Part 5
  • Session 21 - Agile Methodes and practice
  • Session 21 Part 1 - Goal Setting
  • Session 21 Part 2 - SMART goals
  • Session 21 Part 3 - Time Management
  • Minimalist Goal Setting Guide Presentation.pptx
  • SMART Goals Presentation.pptx
  • Session 22 - Statistics fundamentals
  • Session 22 Part 1
  • Session 22 Part 2
  • Session 22 Part 3
  • Session 22 Part 4
  • 17-7-2024.pdf
  • Session 23 - Linear algebra introduction
  • Session 23 Part 1
  • Session 23 Part 2
  • 18-7-2024(Python_Project).pdf
  • PythonPractise.pdf
  • Session 24- Agile
  • Session 24 Part 1 - Update
  • Session 24 Part 2 - Delete , Select
  • Session 24 Part 3 - Filter, ORM
  • Session 24 Part 4 - Connection
  • 19-7-2024.pdf
  • vertopal.com_19-7-2024-task.pdf
  • Session 25 - Advanced linear algebra
  • Session 25 Part 1 - Create Mysql Connection , Design Table , Insert Data into
  • Session 25 Part 2 - Get Data , Search , Bulk Insert
  • Session 25 Part 3 - Insert From Json file , Bulk Updata
  • Session 25 Part 4 - Delete , execute raw sql query
  • vertopal.com_22-7-2024-2.pdf
  • Session 26 - Agile
  • Session 26 Part 1 - Software Engineering
  • Session 26 Part 2 - Agile
  • Session 26 Part 3 - Practice on Flow Chart
  • Session 26 Part 4 - Practice on Flow Chart
  • SW-01.pdf
  • Session 27 -Quiz
  • Session 27 Part 1 - Type , Args , Kwargs
  • Session 27 Part 2 - Export from db to csv
  • Session 27 Part 3 - Allies
  • Session 27 Part 4 - Join ( inner, Left , right )
  • vertopal.com_24-7-2024.pdf
  • Session 28 - Introduction to Numpy and data manipulation
  • Session 28 Part 1 - SDLC Models , Build-and-fix model , Waterfall model
  • Session 28 Part 2 - Evolutionary process models , Rapid prototyping model
  • Session 28 Part 3 - Spiral model , V-shape model
  • Session 28 Part 4 - Incremental model , Agile process model
  • Session 29 -Pandas for data analysis
  • Session 29 Part 1
  • Session 29 Part 2
  • Session 29 Part 3
  • Session 29 Part 4
  • Session 29 Part 5
  • vertopal.com_26-7-2024.pdf
  • Session 30 - Project management tools and techniques
  • Session 30 Part 1
  • Session 30 Part 2
  • Session 30 Part 3
  • Session 30 Part 4
  • Session 30 Part 5
  • Session 30 Part 6
  • vertopal.com_29-7-2024.pdf
  • Session 31 - Data visualization with Matplotlib and Seaborn
  • Session 31 Part 1
  • Session 31 Part 2
  • Session 31 Part 3
  • Session 31 Part 4
  • Session 31 Part 5
  • Data Base Assignmnent
  • Use Case Diagram Task
  • SW02-UseCase.pptx
  • SW02-UseCase.pdf
  • Session 32 -Agile
  • Session 32 Part 1 - Trees
  • Session 32 Part 2 - Hash tables
  • Session 32 Part 3 - Heaps , Graphs
  • Session 32 Part 4 - Leetcode examples
  • 31-7-2024.pdf
  • Session 32 Part 5
  • Session 33 - Exploratory Data Analysis (EDA) techniques
  • Session 33 Part 1
  • Session 33 Part 2
  • Session 33 Part 3
  • Session 33 Part 4
  • Session 33 Part 5
  • SW03-ComponentDiagram.pdf
  • Session 34 - Data analysis project
  • Session 34 Part 1 - Bubble
  • Session 34 Part 2 - Quick
  • Session 34 Part 3 - Merge sort
  • Session 34 Part 4 - Merge sort
  • Session 34 Part 5 - Binary search
  • Session 34 Part 6 - Sliding window
  • Session 35 - Project management tools and techniques
  • Session 35 Part 1
  • Session 35 Part 2
  • Session 35 Part 3
  • Session 35 Part 4
  • Session 35 Part 5
  • SW04-ClassDiagram.pdf
  • Session 36 - Quiz
  • Session 36 Part 1
  • Session 36 Part 2
  • Session 36 Part 3
  • Session 36 Part 4
  • Session 36 Part 5
  • Session 37 - Introduction to Machine Learning
  • Session 37 Part 1 - Kaggle for Data scientists
  • Session 37 Part 2 - Pandas intro , File IO
  • Session 37 Part 3 - Attributes
  • Session 37 Part 4 - Data Cleaning
  • Session 37 Part 5 - Visualization
  • Session 38 - Project management tools and techniques
  • Session 38 Part 1 - Class Diagram
  • Session 38 Part 2 - Class Diagram
  • Session 38 Part 3 - Intro to Data Analysis
  • Session 38 Part 4 - Intro to Data Analysis
  • Session 39 -Supervised learning techniques: regression and classification
  • vertopal.com_02-8-2024.pdf
  • vertopal.com_5-8-2024.pdf
  • 7-8-2024.pdf
  • Session 39 Part 1 - Grouping
  • Session 39 Part 2 - Merge
  • Session 39 Part 3 - Filter
  • Session 39 Part 4 - Deal with text data
  • Session 39 Part 5 - Run notebook in kaggle
  • Session 40 - Unsupervised learning techniques: clustering and association
  • Session 40 Part 1
  • Session 40 Part 2
  • Session 40 Part 3
  • Session 40 Part 4
  • Session 40 Part 5
  • Session 40 Part 6
  • 26-8-2024.pdf
  • Session 41 - Project management skills
  • Session 41 Part 1 - Data Analysis intro
  • Session 41 Part 2 - Probability part 1
  • Session 41 Part 3 - Probability part 1
  • Probability 1.pdf
  • Session 42 - Natural Language Processing (NLP) basics
  • Session 42 Part 1 - Seaborn
  • Session 42 Part 2 - Seaborn
  • Session 42 Part 3 - EDA
  • Session 42 Part 4 - Kaggle
  • Session 42 Part 5 - Competitions
  • Session 42 Part 6 - Markdown
  • 28-8-2024.pdf
  • Session 43 - Project management tools and techniques
  • Session 43 Part 1 - Probability Theorem
  • Session 43 Part 2 - Probability Theorem
  • Session 43 Part 3 - Bayes's Theorem
  • Session 43 Part 4 - Communication Skills
  • Session 43 Part 5 - Communication Skills
  • Session 44 - Machine learning project
  • Session 44 Part 1
  • Session 44 Part 2
  • Session 44 Part 3
  • Session 44 Part 4
  • Session 44 Part 5
  • Session 44 Part 6
  • Session 45 - Neural networks and deep learning concepts
  • Session 45 Part 1
  • Session 45 Part 2
  • Session 45 Part 3
  • Session 45 Part 4
  • Session 45 Part 5
  • Session 45 Part 6
  • Session 45 Part 7
  • 2-9-2024.pdf
  • Session 46 - Design Thinking
  • Session 46 Part 1 - EDA Project Explanation and Discussion
  • Session 46 Part 2 - EDA Project Explanation and Discussion
  • Session 46 Part 3 - EDA Project Explanation and Discussion
  • Session 46 Part 4 - Linear regression and Logistic regression Mathematical
  • Session 47 - Keras and TensorFlow basic
  • Session 47 Part 1
  • Session 47 Part 2
  • Session 47 Part 3
  • Session 47 Part 4
  • Session 47 Part 5
  • Session 47 Part 6
  • Session 47 Part 7
  • 4-9-2024.pdf
  • Session 48 - Design Thinking
  • Session 48 Part 1 - EDA Project 2 Explanation and Discussion
  • Session 48 Part 2 - EDA Project 2 Explanation and Discussion
  • Session 48 Part 3 - EDA Project 2 Explanation and Discussion
  • Session 48 Part 4 - Machine Learning Mathematically explained
  • Session 48 Part 5 - Machine Learning Mathematically explained
  • Session 49 - Advanced TensorFlow
  • Session 49 Part 1
  • Session 49 Part 2
  • Session 49 Part 3
  • Session 49 Part 4
  • Session 49 Part 5
  • Session 49 Part 6
  • 6-9-2024.pdf
  • Session 50 - Convolutional Neural Networks (CNNs)
  • Session 50 Part 1
  • Session 50 Part 2
  • Session 50 Part 3
  • Session 50 Part 4
  • Session 50 Part 5
  • Session 50 Part 6
  • Session 50 Part 7
  • 9-9-2024.pdf
  • Session 51 -Design Thinking
  • Session 51 Part 1
  • Session 51 Part 2
  • Session 51 Part 3
  • Session 51 Part 4
  • Handling_Outliersipynb.pdf
  • Communication and Soft Skills Lec2-Part1.pdf
  • 5. Data Cleaning, and Transformation-Part1.pdf
  • Session 52 - Recurrent Neural Networks (RNNs)
  • Session 52 Part 1
  • Session 52 Part 2
  • Session 52 Part 3
  • Session 52 Part 4
  • Session 52 Part 5
  • 11-9-2024.pdf
  • Session 53 - Design Thinking
  • Session 53 Part 1
  • Session 53 Part 2
  • Session 53 Part 3
  • Session 53 Part 4
  • Session 54 - Long Short-Term Memory (LSTM) networks
  • Session 54 Part 1
  • Session 54 Part 2
  • Session 54 Part 3
  • ml-project..pdf
  • 13-9-2024-1.pdf
  • Session 55 - Transfer learning
  • Session 55 Part 1
  • Session 55 Part 2
  • Session 55 Part 3
  • Session 55 Part 4
  • Session 55 Part 5
  • 16-9-2024..pdf
  • Session 56 - Creative Thinking
  • Session 56 Part 1
  • Session 56 Part 2
  • Session 56 Part 3
  • Session 56 Part 4
  • Communication and Soft Skills Lec2-Part2.pdf
  • Session 57 - Deep learning project
  • Session 57 Part 1
  • Session 57 Part 2
  • Session 57 Part 3
  • Session 57 Part 4
  • Session 57 Part 5
  • Session 57 Part 6
  • 18-9-2024.pdf
  • Session 58 - Creative Thinking
  • Session 58 Part 1
  • Session 58 Part 2
  • Session 58 Part 3
  • Session 58 Part 4
  • Session 58 Part 5
  • Session 59 - Introduction to Generative AI
  • Session 59 Part 1
  • Session 59 Part 2
  • Session 59 Part 3
  • Session 59 Part 4
  • Session 59 Part 5
  • 20-9-2024-1.pdf
  • 20-9-2024.pdf
  • Session 60 - Image generation with Img2Img
  • Session 60 Part 1
  • Session 60 Part 2
  • Session 60 Part 3
  • Session 60 Part 4
  • Session 60 Part 5
  • 23-9-2024.pdf
  • Session 61 - Basic German for Tech Professionals
  • Session 61 Part 1 - Open discussion about deep learning
  • Session 61 Part 2 - thirty important DAX function in Power BI - Part 1
  • Session 61 Part 3 - thirty important DAX function in Power BI - Part 2
  • Session 61 Part 4 - Practical
  • Session 61 Part 5 - Practical
  • DAX_Functions_30_Presentation.pdf
  • Session 62 - Multi-model integration
  • Session 62 Part 1
  • Session 62 Part 2
  • Session 62 Part 3
  • Session 62 Part 4
  • Session 62 Part 5
  • 25-9-2024.pdf
  • emotion-detection-cnn-transfer-learning.pdf
  • Session 63 - Basic German for Tech Professionals
  • Session 63 Part 1
  • Session 63 Part 2
  • Session 63 Part 3
  • Session 63 Part 4
  • Session 63 Part 5
  • Session 63 Part 6
  • 26-9-202.pdf
  • Session 64 - Large Language Models (LLMs)
  • Session 64 Part 1
  • Session 64 Part 2
  • Session 64 Part 3
  • Session 64 Part 4
  • Session 64 Part 5
  • 27-9-2024.pdf
  • Session 65 - Fine-tuning models
  • Session 65 Part 1
  • Session 65 Part 2
  • Session 65 Part 3
  • Session 65 Part 4
  • Session 65 Part 5
  • 30-9-2024.pdf
  • Session 66 - Basic German for Tech Professionals
  • Session 66 Part 1
  • Session 66 Part 2
  • Session 66 Part 3
  • Session 66 Part 4
  • Time Management Lec1.pdf
  • Session 67 - OpenAI tools and applications Practical Projects
  • Session 67 Part 1
  • Session 67 Part 2
  • Session 67 Part 3
  • Session 67 Part 4
  • Session 67 Part 5
  • 2-10-OpenAI tools and applications.pdf
  • DL Interview.pdf
  • ML Interview.pdf
  • Session 68 -Langchain & Llamaindex & Ollama basics
  • Session 68 Part 1
  • Session 68 Part 2
  • Session 68 Part 3
  • Session 68 Part 4
  • Session 68 Part 5
  • Session 69 -Vector Databases
  • Session 69 Part 1
  • Session 69 Part 2
  • Session 69 Part 3
  • Session 69 Part 4
  • Session 69 Part 5
  • Session 69 Part 6
  • 4-10-Langchain and llamaIndex.pdf
  • Session 70 -Intermediate German for Tech Professionals
  • Session 70 Part 1
  • Session 70 Part 2 - Time Managment Lec 2
  • Session 70 Part 3 - Z-score Test
  • Session 70 Part 4 - Mcnemar Test
  • Time Management Lec2.pptx
  • 7-10-Vector DB.pdf
  • Session 71 - Generative AI Project
  • Session 71 Part 1
  • Session 71 Part 2
  • Session 71 Part 3
  • Session 71 Part 4
  • Session 71 Part 5
  • Session 72 - Intermediate German for Tech Professionals
  • Session 72 Part 1
  • Session 72 Part 2
  • Session 72 Part 3
  • RACI_Matrix_Exercise.docx
  • assignment_1728566759
  • Session 72 Part 4
  • Session 73 -MLOps Intro
  • Session 73 Part 1
  • Session 73 Part 2
  • Session 73 Part 3
  • Session 73 Part 4
  • Session 74 - Quiz
  • Session 74 Part 1
  • Session 74 Part 2
  • Session 74 Part 3
  • Session 74 Part 4
  • 11-10-2024-Generative AI project.pdf
  • Session 75 - Intermediate German for Tech Professionals
  • Session 75 Part 1
  • Session 75 Part 2
  • Session 75 Part 3
  • Session 75 Part 4
  • Session 76 - Version Control git & github
  • Session 76 Part 1
  • Session 76 Part 2
  • Session 76 Part 3
  • Session 76 Part 4
  • Session 77 - German for job applications and CV writing
  • Session 77 Part 1
  • Session 77 Part 2
  • Project Management Lecture 3.pdf
  • Resource_Plan_Template_ProjectManager.xlsx
  • Session 78 - Containerization with Docker
  • Session 78 Part 1
  • Session 78 Part 2
  • Session 78 Part 3
  • Session 78 Part 4
  • Session 78 Part 5
  • Session 79 -Frontend Basics
  • Session 79 Part 1
  • Session 79 Part 2
  • Session 79 Part 3
  • Session 79 Part 4
  • Session 79 Part 5
  • Session 80 -German for job applications and CV writing
  • ML Project - Smoker Detector
  • Session 80 Part 1 - Ml Project 1
  • Session 80 Part 2 - Ml project 2
  • Session 80 Part 3 - Risk Managmenet
  • Session 81 - -Backend development with FastAPI
  • Session 81 Part 1
  • Session 81 Part 2
  • Session 81 Part 3
  • Session 81 Part 4
  • Session 81 Part 5
  • Session 82 -German for job applications and CV writing
  • Session 82 Part 1 - HTML Recap
  • Session 82 Part 2 -German for job applications and CV writing
  • Session 82 Part 3 - Finalizing Project ( Team Work )
  • Session 83 -Flask for web applications (8 units)
  • Session 83 Part 1
  • Session 83 Part 2
  • Session 83 Part 3
  • Session 83 Part 4
  • Session 83 Part 5
  • Session 84 -Streamlit for data apps (8 units)
  • Session 84 Part 1
  • Session 84 Part 2
  • Session 84 Part 3
  • Session 84 Part 4
  • Session 84 Part 5
  • Session 85 Project Managmnet ( Application )
  • Session 85 Part 1 - Fast API Recap
  • Session 85 Part 2 -German for job applications and CV writing
  • Session 86 -MlFlow for model management (8 units)
  • Session 86 Part 1
  • Session 86 Part 3
  • Session 86 Part 4
  • Session 86 Part 2
  • Session 87Resume and cover letter workshops
  • Session 87 Part 1
  • Session 87 Part 2
  • Session 87 Part 3
  • Session 87 Part 4
  • Session 87 Part 5
  • Session 88 -Monitoring and debugging ML systems (8 units)
  • Session 88 Part 1
  • Session 88 Part 2
  • Session 88 Part 3
  • Session 88 Part 4
  • Session 89 - Resume and cover letter workshops
  • Session 88 Part 5
  • Session 89 Part 1 - Ollama Project part 1
  • Session 89 Part 2 - Ollama Project Part 2
  • Session 89 Part 3 - Agile Lec 1 Part 1
  • Session 89 Part 4 - Agile Lec 2 Part 2
  • Resume and cover letter workshops
  • Session 90 - CI/CD pipelines (8 units)
  • Session 90 Part 1
  • Session 90 Part 2
  • Session 90 Part 3
  • Session 90 Part 4
  • Session 90 Part 5
  • Session 91 -Resume and cover letter workshops
  • Session 91 Part 1 - Resume and cover letter workshops
  • Session 91 Part 2 - Tasks Discussion
  • Session 91 Part 3 - Scrum Framework
  • Resume and cover letter workshops
  • Session 92 - Production deployment (8 units)
  • Session 92 Part 1
  • Session 92 Part 2
  • Session 92 Part 3
  • Session 92 Part 4
  • Session 92 Part 5
  • Session 93 - Azure AI Studio (8 units)
  • Session 93 Part 1
  • Session 93 Part 2
  • Session 93 Part 3
  • Session 93 Part 4
  • Session 94 - Resume and cover letter workshops
  • Agile Lec 3
  • Session 94 Part 1
  • Session 94 Part 2
  • Session 94 Part 3
  • Session 94 Part 4
  • Session 95 - Amazon Bedrock (8 units
  • Session 95 Part 1
  • Session 95 Part 2
  • Session 95 Part 3
  • Session 95 Part 4
  • Session 95 Part 5
  • Session 95 Part 6
  • Session 96 - German for job applications and CV writing
  • Agile Lec 4
  • Session 96 Part 1 - Student's project Work
  • Session 96 Part 2
  • Session 96 Part 3
  • Session 96 Part 4
  • Session 97 -MLOps project (8 units)
  • Session 97 Part 1
  • Session 97 Part 2
  • Session 97 Part 3 - Basic German
  • Session 97 Part 4 - Basic German
  • Basic German for Tech professionals 
  • Session 98 -Transformer’s introduction (8 units)
  • Session 98 Part 1
  • Session 98 Part 2
  • Session 98 Part 3
  • Session 98 Part 4
  • Session 99 -BERT and other transformer models (8 units)
  • Session 99 Part 1
  • Session 99 Part 2
  • Session 99 Part 3
  • Session 100 -German for job applications and CV writing
  • Session 100 Part 1 -
  • Session 100 Part 2
  • Session 100 Part 3
  • Session 101 - Advanced NLP techniques (8 units)
  • Session 101 Part 1
  • Session 101 Part 2
  • Session 101 Part 3
  • Session 101 Part 4
  • Session 102 -German for job applications and CV writingts)
  • Session 102 Part 1
  • Session 102 Part 2
  • Session 102 Part 3
  • Session 102 Part 4
  • Session 102 Part 5
  • Session 103 -Computer vision applications (8 units)
  • Session 103 Part 1
  • Session 103 Part 2
  • Session 103 Part 3
  • Session 103 Part 4
  • Session 104 - German for job applications and CV writing
  • Session 104 Part 1
  • Session 104 Part 2
  • Session 104 Part 3
  • Session 104 Part 4
  • Agil
  • Agile Lecture 4
  • Agile Lecture 5
  • Agile lecture 6
  • Session 105 -Advanced computer vision techniques (8 units)
  • Session 105 Part 1
  • Session 105 Part 2
  • Session 105 Part 3
  • Session 105 Part 4
  • Session 105 Part 5
  • Session 106 - AI ethics and bias (8 units)
  • Session 106 Part 1
  • Session 106 Part 2
  • Session 106 Part 3
  • Session 106 Part 4
  • Session 106 Part 5
  • Session 107 -AI security (8 units)
  • Session 107 Part 1
  • Session 107 Part 2
  • Session 107 Part 3
  • Session 108 -Quiz
  • Session 108 Part 1
  • Session 108 Part 2
  • Session 108 Part 3
  • Session 108 Part 4
  • Session 109 Interview skills and job search strategies
  • Session 109 Part 1
  • Session 109 Part 2
  • Session 109 Part 3
  • Session 109 Part 4
  • Session 109 Part 5
  • Interview Skills part 1
  • Interview skills part 2
  • Interview Skills part 3
  • Session 110 - Project ideation and planning (8 units)
  • Session 110 Part 1
  • Session 110 Part 2
  • Session 110 Part 3
  • Session 110 Part 4
  • Session 110 Part 5
  • Session 111 -Interview skills and job search strategies
  • Session 111 Part 1
  • Session 111 Part 2
  • Session 111 Part 3
  • Session 112 - Data collection and preprocessing (8 units)
  • Session 112 Part 1
  • Session 112 Part 2
  • Session 112 Part 3
  • Session 112 Part 4
  • Session 112 Part 5
  • Session 113 - Building and training models (8 units)
  • Session 113 Part 1
  • Session 113 Part 2
  • Session 113 Part 3
  • Session 113 Part 4
  • Session 114 - Interview Skills assessment & Design thinking
  • Session 114 Part 1
  • Session 114 Part 2
  • Session 114 Part 3
  • Session 114 Part 4
  • Session 115 - Model evaluation and refinement (8 units)
  • Session 115 Part 1
  • Session 115 Part 2
  • Session 115 Part 3
  • Session 115 Part 4
  • Session 115 Part 5
  • Session 116 Frontend and backend integration (8 units)
  • Session 116 Part 1
  • Session 116 Part 2
  • Session 116 Part 3
  • Session 116 Part 4
  • Session 116 Part 5
  • Session 117 - Final project presentations
  • Session 117 Part 1
  • Session 117 Part 2
  • Session 117 Part 3
  • Session 117 Part 4
  • Session 117 Part 5
  • Session 118 - Interview skills and job search strategies
  • Session 118 Part 1
  • Session 118 Part 2
  • Session 118 Part 3
  • Session 118 Part 4
  • Session 118 Part 5
  • Session 119 -Interview skills and job search strategies
  • Session 119 Part 1
  • Session 119 Part 2
  • Session 119 Part 3 -DIN 5008 in cover letter&Cover letters example
  • Session 119 Part 4 - Personalities test and feedback & Analysis on vacancys
  • Session 120 - Arbeiten mit BA Jobbörse BERUFNET und Profilerstellung
  • Session 120 Part 1
  • Session 120 Part 2
  • Session 120 Part 3- CV creating & LinkedIn use for succesful career
  • Session 120 Part 4- analyse of vacancys & intro jobbörse der BA
  • Session 121 - Interview skills and job search strategies
  • Session 121 Part 1
  • Session 121 Part 2
  • Session 121 Part 3 -Using EGZ as a plus to find a job
  • Session 121 Part 4 - Preparing a new and useful CV including all updates
  • Session 122 -Arbeiten mit BA Jobbörse BERUFNET und Profilerstellung
  • Session 122 Part 1
  • Session 122 Part 2
  • Session 122 Part 3
  • Session 122 Part 4 - sing ChatGPT & Continie work on the CV renew and update
  • Session 122 Part 5 - LinkedIn Profil for more job options
  • Session 123 - Professional online presence and networking
  • Session 123 Part 1
  • Session 123 Part 2
  • Session 123 Part 3
  • Session 123 Part 4
  • Session 123 Part 5 - LinkedIn Profil for more job & Add Skills to LinkedIn
  • Session 123 Part 6 - Unique CV Check & Introduction in job interview
  • Session 124 Professional online presence and networking
  • Session 124 Part 1
  • Session 124 Part 2
  • Session 124 Part 3
  • Session 124 Part 4
  • Session 125 -Rückblick Maßnahme und Beendigung
  • Session 125 Part 1
  • Session 125 Part 2
  • Session 125 Part 3
  • Session 125 Part 4
  • Session 125 Part 5 - using Chat GPT to form a cover letter
  • Session 125 Part 6 -create a cover letter for your favorite job and apply for it
Completion rules
  • All units must be completed
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