Mentor for PLC and AI Training with python

Job Description:

I am looking for an experienced Python developer and tutor to provide me with comprehensive, one-on-one training. My ultimate goal is to learn how to read data from a PLC (Programmable Logic Controller), analyze it using a custom fine-tuned AI model, and send the results back to the PLC, all using Python.

I am an absolute beginner in Python and programming. I need a tutor who can build my knowledge from the ground up, focusing on the practical skills required for this specific industrial automation and AI integration project.

Scope of Work & Learning Objectives:

The tutor will be responsible for designing a complete curriculum and teaching me the following modules in sequence:

1. Python Fundamentals (Core Syntax & Concepts):

Variables, data types (integers, floats, strings, booleans), and basic operations.

Data structures crucial for data handling: Lists, Dictionaries, Tuples.

Control flow: If/Else statements, For loops, While loops.

Functions: Defining functions, parameters, return values.

Working with libraries/modules (using pip to install).

Basic file I/O (reading/writing text files, CSVs).

2. Python for Industrial Communication (PLC Data Handling):

How to use key Python libraries for industrial protocols:

pymodbus (for Modbus TCP/IP)

python-snap7 (for Siemens S7)

opcua (for OPC UA)

Establishing a connection to a PLC (simulated or real) from Python.

Reading data from PLC registers (Holding Registers, Input Registers, DBs).

Writing data back to PLC registers.

Handling errors and connection timeouts gracefully.

3. Python for Data Science & AI Model Integration:

Using NumPy for numerical data manipulation.

Using Pandas for data analysis and structuring the data received from the PLC.

Basics of data preprocessing: normalization, scaling, formatting data for AI model input.

Loading a pre-trained, fine-tuned AI model (e.g., a TensorFlow/Keras or PyTorch model saved in .h5 or .pt format).

Performing inference (making predictions) on the PLC data using the loaded model.

Post-processing the model's output into a format the PLC can understand.

4. Full Integration & Project Architecture:

Designing the main program loop: Read -> Preprocess -> Predict -> Postprocess -> Write.

Implementing timing and scheduling (e.g., using time.sleep() or advanced schedulers).

Best practices for writing clean, maintainable, and robust code for industrial environments.

Basic debugging and logging.

Requirements for the Tutor/Freelancer:

Must be Fluent in English. Communication is key.

Proven Expertise in Python, especially in the areas mentioned above.

Hands-on Experience with at least one PLC communication library (pymodbus, snap7, etc.). Experience with actual hardware is a huge plus.

Practical Experience with AI/ML libraries like TensorFlow, PyTorch, or Scikit-learn. You must be able to explain how to load a model and use it for prediction.

Patience and Teaching Ability: You must be able to explain complex concepts to a beginner clearly and without jargon. You should provide simple examples, exercises, and real-world analogies.

Availability for multiple scheduled sessions per week via video call (e.g., Zoom, Google Meet).

Project Type: One-on-One Lessons / Ongoing Tutoring

How do you want to receive the lessons?: Video conference