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Certificates: Certificate "AI Manager with TÜV Rheinland certified qualification"
Certificate "PCEP™ - Certified Entry-Level Python Programmer"
Certificate "Relational Databases SQL" -
Examination: Praxisbezogene Projektarbeiten mit Abschlusspräsentationen
KI-Manager:in mit TÜV Rheinland geprüfter Qualifikation
Certified Entry-Level Python Programmer (PCEP™) (in englischer Sprache) -
Teaching Times: Full-timeMonday to Friday from 8:30 a.m. to 3:35 p.m. (in weeks with public holidays from 8:30 a.m. to 5:10 p.m.)
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Language of Instruction: German
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Duration: 12 Weeks
Artificial intelligence: AI manager with TÜV Rheinland-certified qualification
Fundamentals of operational AI projects (approx. 5 days)
Introduction to AI, ML, DL, NLP and computer vision (operational focus)
Roles and tasks: Setting up, operating and reviewing the effectiveness of the management system in accordance with ISO 42001
Role delineation and collaboration: AI officer, AI manager and AI auditor
Identification and evaluation of operational use cases in the company
Project initiation: target definition, scope, feasibility analysis
Stakeholder management
Value creation and ROI through AI
Successful AI initiatives in management
Data management and use of tools (approx. 3 days)
Data preparation, quality and integration
Selection and implementation of AI tools and platforms
Practical prompting for text, image and video applications
Building simple data pipelines
Introduction to MLOps concepts
AI automation options in operation
Model training, validation and use (approx. 2 days)
Training and validation of models
Test procedures: Black box, white box, unit tests
Use of models
Monitoring and iterative optimization
Integration of AI agents in projects
Risk management and quality assurance (approx. 2 days)
Technical risk analysis: bias metrics, fairness tests, model error analysis
Quality assurance: KPIs, monitoring, acceptance processes
Management system according to ISO 42001
Security and explainability of AI systems
Operational project management and agile methods (approx. 2 days)
Agile methods: Scrum, Kanban, iterative deployment cycles
Resource and budget planning
Team and stakeholder communication
Ongoing optimization and problem-solving strategies (CIP)
Cooperation with external partners
Organizational development, governance and change management (approx. 3 days)
Analysis of business processes
Maturity level analysis, GAP analysis
Creation of an AI roadmap
AI governance and strategy development
Development of a sustainable organizational structure
Responsibilities
Practical handling of resistance in AI operations
Sustainability and corporate digital responsibility (CDR)
Project work, certification preparation and certification exam "AI Manager with TÜV Rheinland certified qualification" (approx. 3 days)
Programming with Python
Python basics (approx. 1 day)
History, concepts
Usage and areas of application
syntax
Lexis, semantics
PEP-8 conventions
Interpreter vs. compiler
Numeral systems: binary, octal, hexadecimal
Scientific Notation
First steps with Python (approx. 5 days)
Numbers
Strings
Date and time
Standard input and output
Numeric operators
Comparison, logical and bitwise operators
Data type conversion
list, tuple, dict, set
List functions and methods
Branching and loops (if, for, while)
Member operators
String basics: escaping, multiline strings
Prioritizing and binding operators
Artificial intelligence (AI) in the work process
Presentation of specific AI technologies
and possible applications in the professional environment
Functions (approx. 5 days)
Define your own functions
Variables
Parameters and arguments
Return values
Recursion
Namespaces
Functional programming
Parameter types: positional, keyword, mixed
Default values
Shadowing and global keyword
None and return without value
Troubleshooting (approx. 0.5 days)
Basics of error handling with try and except
Typical error types and exception hierarchy
Error propagation and program interruptions
Structuring the except blocks
Object-oriented programming (approx. 4.5 days)
Python classes
Methods
Immutable objects
Data class
Inheritance
Project work, certification preparation and certification exam "PCEP™ - Certified Entry-Level Python Programmer" in English (approx. 4 days)
Relational databases with SQL
Basics of database systems and SQL (approx. 3 days)
Overview of database systems and models
Redundant data and data integrity
Normalization
Database design and entity relationship model (ERM)
Primary and foreign keys
Relationships between relations
Data types in SQL
Indexes and performance
Constraints and validation
Queries in SQL
Structured data as the basis for AI-supported analysis methods
Introduction to SQL Server Management Studio (SSMS) (approx. 2 days)
Overview of SQL Server and SSMS
Physical database design
Creating tables and defining data types
Constraints, default values and relationships
Database diagrams (ERM) and relationships
Backup and restore
Introduction to performance monitoring
Overview of AI-supported query optimization and query analysis
Introduction to DDL (Data Definition Language) and DML (Data Manipulation Language) (approx. 8 days)
SQL basics and extended syntax
Operators and integrated functions
Queries and manipulation of data
Error handling and transaction management
Creation and administration of database objects
Basics of performance optimization
Working with modern data types
Data modeling and structured preparation for AI and analysis applications
DCL - Data Control Language and Security (approx. 1 day)
User administration and authorizations
Roles and security concepts
Auditing
Introduction to Row Level Security
Data security in the context of AI-supported evaluations
Data types, data import and export in modern systems (approx. 1 day)
Data import and export
Modern data types
Import, transformation and provision of data for analysis processes
Project work (approx. 5 days)
To consolidate the content learned
Presentation of the project results
Changes are possible, the course content is updated regularly.
After the course, you will be able to plan and implement AI-supported transformation projects in line with standards and anchor them sustainably in your company. You will be able to maximize the economic benefits, value creation and ROI of AI initiatives, take risks and compliance requirements into account and establish a sustainable organizational structure, governance and change management strategies for the successful use of AI.
You also have a compact, basic knowledge of programming with Python and are confident in using the programming language with its classes, libraries and functions.
You can also develop and manage relational databases with SQL. You will create tables and views, formulate queries and process data with suitable SQL commands. You will pay attention to data integrity, use transactions and assign user rights in SQL Server. You will also prepare structured data for analysis and AI-supported evaluations.
This course is aimed at specialists, managers and project managers from all areas of the company who are involved in digitally networked, global work structures and want to use AI technologies to make processes and decisions more efficient.
Specialists and managers who want to drive their companies forward in the digital transformation and can use AI as a tool to improve efficiency, decision-making and innovation in companies are in demand in all sectors.
In addition, the versatility of Python makes employees with the relevant skills attractive in numerous industries and companies. People with programming skills in Python are particularly sought after in web development, machine learning and data analysis.
By creating and developing databases, companies ensure efficient sorting, logical structuring and permanent documentation of important data. Additional knowledge as an SQL database specialist or administrator will complement your knowledge accordingly and round off your profile.
Didactic concept
Your lecturers are highly qualified both professionally and didactically and will teach you from the first to the last day (no self-study system).
You will learn in effective small groups. The courses usually consist of 6 to 25 participants. The general lessons are supplemented by numerous practical exercises in all course modules. The practice phase is an important part of the course, as it is during this time that you process what you have just learned and gain confidence and routine in its application. The final section of the course involves a project, a case study or a final exam.
Virtual classroom alfaview®
Lessons take place using modern alfaview® video technology - either from the comfort of your own home or at our premises at Bildungszentrum. The entire course can see each other face-to-face via alfaview®, communicate with each other in lip-sync voice quality and work on joint projects. Of course, you can also see and talk to your connected trainers live at any time and you will be taught by your lecturers in real time for the entire duration of the course. The lessons are not e-learning, but real live face-to-face lessons via video technology.
The courses at alfatraining are funded by Agentur für Arbeit and are certified in accordance with the AZAV approval regulation. When submitting a Bildungsgutscheinor Aktivierungs- und Vermittlungsgutschein, the entire course costs are usually covered by your funding body.
Funding is also possible via Europäischen Sozialfonds (ESF), Deutsche Rentenversicherung (DRV) or regional funding programs. As a regular soldier, you have the option of attending further training courses via Berufsförderungsdienst (BFD). Companies can also have their employees qualified via funding from Agentur für Arbeit (Qualifizierungschancengesetz).