Prompte engneering using python and Large Language Models (LLMs)

Van 40.63 $ /h

### Course Description: Prompt Engineering using Python and LLMs

Unlock the power of Large Language Models (LLMs) with our beginner-friendly course, "Prompt Engineering using Python and LLMs." This course is designed to introduce you to the fundamentals of prompt engineering, equipping you with the skills needed to craft effective prompts and leverage the capabilities of LLMs for various applications.

#### Course Objectives:
- **Introduction to Prompt Engineering:** Understand the basics of prompt engineering and its significance in utilizing LLMs.
- **Python for Prompt Engineering:** Learn essential Python programming skills tailored for prompt engineering tasks.
- **Harnessing LLMs:** Discover how to use LLMs to generate, manipulate, and analyze text based on your crafted prompts.
- **Practical Applications:** Apply your knowledge through hands-on projects and real-world scenarios to build practical solutions.

#### Course Outline:
1. **Introduction to Prompt Engineering:**
- What is prompt engineering?
- Importance and applications of prompt engineering
- Overview of Large Language Models (LLMs) and their capabilities

2. **Python Essentials for Prompt Engineering:**
- Basic Python programming concepts
- Key Python libraries for text processing
- Setting up your development environment

3. **Crafting Effective Prompts:**
- Understanding prompt structure and components
- Techniques for creating clear and concise prompts
- Examples of effective prompts for various tasks

4. **Interacting with LLMs:**
- Introduction to popular LLMs (e.g., GPT-3, GPT-4)
- Using APIs to interact with LLMs
- Generating text responses based on your prompts

5. **Advanced Prompt Techniques:**
- Handling complex queries and multi-step instructions
- Refining prompts for improved accuracy and relevance
- Using prompts for different applications (e.g., content generation, data analysis)

6. **Practical Projects:**
- Building a text generation application
- Creating a chatbot using prompt engineering techniques
- Developing a data extraction tool using LLMs

7. **Ethical Considerations and Best Practices:**
- Ensuring ethical use of LLMs and prompt engineering
- Best practices for responsible AI development
- Avoiding common pitfalls and challenges

8. **Future Directions and Further Learning:**
- Exploring advanced topics in prompt engineering
- Keeping up with the latest advancements in LLMs
- Resources for continued learning and development

#### Who Should Enroll:
- Beginners with no prior experience in prompt engineering or LLMs
- Individuals interested in learning Python programming
- Aspiring AI enthusiasts looking to explore the potential of LLMs

#### Prerequisites:
- Basic computer literacy and familiarity with high school-level mathematics
- No prior programming or AI experience required

#### Course Outcomes:
By the end of this course, you will be able to:
- Understand the fundamentals of prompt engineering
- Write and execute Python code for prompt engineering tasks
- Create effective prompts to interact with LLMs
- Develop practical applications using LLMs
- Apply ethical considerations and best practices in your work

Join us in "Prompt Engineering using Python and LLMs" to embark on your journey into the world of AI and prompt engineering. Gain the skills and confidence needed to create impactful solutions and unlock the full potential of Large Language Models.

Extra informatie

bring your laptop

Locatie

Online vanuit Canada

Over

Programming with several programming languages, such as C, JAVA, and Python.
Data scientist: extracting knowledge from structured, semi-structured, and unstructured data.
Teach programming languages and data science.
Five years of experience in teaching.

Opleiding

Ph.D. in Artificial Intelligence Multi-modal from Sidi Mohamed Ben Abdellah University.
Master's degree in Big Data analytics and smart systems, from Sidi Mohamed Ben Abdellah University.
Bachelor's degree in Computer Science and Mathematics from Ibn Zohr University

Leservaring

Five years of experience in teaching.
Freelancer in several programming projects.

Leeftijd

Kinderen (7-12 jaar oud)

Tieners (13-17 jaar oud)

Volwassenen (18-64 jaar oud)

Senioren (65+ jaar oud)

Niveau van de leerling

Beginner

Gemiddeld

Gevorderden

Duur

60 minuten

De les wordt gegeven in

Engels

Arabisch

Frans

Vaardigheden

Python

Computer programmeren

Beschikbaarheid typische week

(GMT -05:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Teaching the Programming language(JAVA, Python, C, JavaScript)

23.9 $ /h

### Course Description: Teaching the Programming Languages (JAVA, Python, C, JavaScript)

Welcome to the comprehensive course on Teaching the Programming Languages: JAVA, Python, C, and JavaScript. This course is designed for aspiring programmers and educators who aim to master the fundamentals and advanced concepts of four of the most popular programming languages in the industry.

#### Course Objectives:
- **Introduction to Programming Concepts:** Understand the core principles of programming, including variables, data types, control structures, functions, and algorithms.
- **Language-Specific Syntax and Features:** Gain proficiency in the syntax and unique features of JAVA, Python, C, and JavaScript.
- **Hands-On Coding Practice:** Apply your knowledge through numerous coding exercises, projects, and real-world scenarios.
- **Debugging and Problem-Solving:** Develop strong debugging and problem-solving skills to efficiently resolve coding issues.
- **Advanced Topics:** Explore advanced topics such as object-oriented programming, web development, data structures, and algorithms.
- **Teaching Methodologies:** Learn effective teaching strategies to impart programming knowledge to others, whether in a classroom setting or online.

#### Course Outline:
1. **Introduction to Programming:**
- Basics of programming and computational thinking
- Overview of the four languages: JAVA, Python, C, and JavaScript

2. **JAVA Programming:**
- Syntax and basic constructs
- Object-oriented programming concepts
- Exception handling and multithreading
- Building GUI applications

3. **Python Programming:**
- Syntax and basic constructs
- Data structures and libraries
- Functional programming and modules
- Web development with Flask/Django

4. **C Programming:**
- Syntax and basic constructs
- Memory management and pointers
- File handling and system programming
- Data structures and algorithm implementation

5. **JavaScript Programming:**
- Syntax and basic constructs
- DOM manipulation and event handling
- Asynchronous programming and AJAX
- Front-end frameworks (React, Angular, or Vue.js)

6. **Integrated Projects:**
- Cross-language projects to solidify understanding
- Real-world applications and problem-solving

7. **Teaching Strategies:**
- Curriculum development and lesson planning
- Interactive and engaging teaching methods
- Assessment and feedback techniques

#### Who Should Enroll:
- Aspiring programmers who want to learn multiple programming languages
- Educators and trainers looking to enhance their teaching skills
- Professionals seeking to expand their coding expertise for career advancement

#### Prerequisites:
- Basic understanding of computer operations
- No prior programming experience required, but familiarity with basic programming concepts is beneficial

#### Course Outcomes:
By the end of this course, you will be able to:
- Write, debug, and optimize code in JAVA, Python, C, and JavaScript
- Develop comprehensive projects using each language
- Effectively teach programming concepts to others
- Apply advanced programming techniques to solve complex problems

Join us in this journey to become proficient in four powerful programming languages and enhance your teaching abilities to inspire the next generation of coders.

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AI and data science (the steps to handle a project)

31.07 $ /h

Embark on a comprehensive journey through Artificial Intelligence and Data Science with our course, "AI and Data Science: The Steps to Handle a Project." This course is meticulously designed for individuals who aspire to become proficient in managing and executing AI and data science projects from inception to deployment.

#### Course Objectives:
- **Foundational Knowledge:** Understand the core principles of AI and data science, including key concepts, methodologies, and tools.
- **Project Lifecycle Management:** Learn the systematic approach to handling AI and data science projects through each project lifecycle phase.
- **Hands-On Experience:** Gain practical experience through real-world projects and case studies.
- **Advanced Techniques:** Explore advanced techniques and algorithms in AI and data science.
- **Ethical and Responsible AI:** Understand the ethical implications and best practices for responsible AI development and deployment.

#### Course Outline:
1. **Introduction to AI and Data Science:**
- Overview of AI and data science
- Key concepts and terminologies
- Applications and industry use cases

2. **Project Scoping and Planning:**
- Defining the problem statement
- Identifying objectives and success metrics
- Project planning and timeline management

3. **Data Collection and Preprocessing:**
- Data collection methods and sources
- Data cleaning, transformation, and integration
- Exploratory data analysis and visualization

4. **Model Development:**
- Selection of appropriate algorithms and models
- Training, validation, and testing of models
- Hyperparameter tuning and optimization

5. **Model Evaluation and Validation:**
- Evaluation metrics and performance analysis
- Cross-validation techniques
- Model interpretability and explainability

6. **Deployment and Monitoring:**
- Model deployment strategies and tools
- Monitoring and maintaining model performance
- Continuous integration and continuous deployment (CI/CD)

7. **Project Documentation and Presentation:**
- Creating comprehensive project documentation
- Presenting findings and insights to stakeholders
- Effective communication of technical results

8. **Ethics and Best Practices:**
- Ethical considerations in AI and data science
- Ensuring fairness, accountability, and transparency
- Best practices for sustainable and responsible AI

#### Course Outcomes:
By the end of this course, you will be able to:
- Manage and execute AI and data science projects from start to finish
- Collect, preprocess, and analyze data effectively
- Develop, evaluate, and deploy robust AI models
- Communicate insights and results clearly to stakeholders
- Apply ethical and responsible practices in AI development

Join us to master the end-to-end process of handling AI and data science projects and become a proficient practitioner capable of delivering impactful solutions.

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Manoj

4.95

(21)

I am a Professional Full Stack Developer with over 15 years of hands-on experience in software engineering, system design, and artificial intelligence.
I’ve worked across frontend, backend, DevOps, and AI, building enterprise-grade systems for real-world applications — from large-scale microservices to cognitive AI platforms.

I’m passionate about teaching the real, modern way of coding — combining deep technical foundations with today’s most advanced technologies: Generative AI, Agentic systems, RAG architectures, cloud automation, and intelligent DevOps.

Whether you are a beginner exploring your first “Hello World,” a professional improving your stack, or a researcher/developer exploring AI systems, I can guide you step-by-step — conceptually, practically, and strategically.

🧩 What You Will Learn
🖥️ Front-End Development

Master how to build responsive, interactive, and high-performance interfaces:

HTML / HTML5 – Structure, semantics, forms, accessibility

CSS / CSS3 / SCSS – Layout, animations, responsive design, Flexbox, Grid

Bootstrap / Tailwind / Material UI – Rapid design frameworks

JavaScript (ES6+) – Functional programming, event loop, closures, async/await

TypeScript – Strong typing, interfaces, decorators, generics

React.js / Next.js – Components, hooks, state management, routing, APIs

Angular (1.x to 17) – Modules, dependency injection, RxJS, advanced architecture

Vue.js (optional) – Reactive programming, lifecycle management

jQuery / AJAX – Legacy support and backend communication

Web Performance – Lighthouse, Core Web Vitals, PWA, caching strategies

⚙️ Back-End & Enterprise Development

Build scalable, secure, and intelligent server-side systems:

C / C++ / Data Structures / Algorithms / OOPS

Java / J2EE / Spring / Spring Boot / Spring Cloud / Hibernate / Struts / Wicket

Microservices Architecture – API gateway, service registry, inter-service communication

Node.js / Express / NestJS – Modern JavaScript/TypeScript backend

REST & SOAP Web Services – API design, security, documentation (Swagger / Postman)

Python (Flask / FastAPI) – REST APIs, ML pipelines, automation

Shell Scripting (Linux/Unix) – Automation, cron jobs, log parsing, DevOps scripting

PHP / Laravel / CodeIgniter – Classic web backend development

Containerization & Orchestration: Docker, Kubernetes, Helm

CI/CD & Cloud: Jenkins, GitHub Actions, Azure DevOps Pipelines

☁️ Cloud & DevOps Mastery

Learn to build, deploy, and scale applications on the cloud:

AWS (EC2, S3, Lambda, DynamoDB, API Gateway, ECS)

Azure (App Services, Functions, CosmosDB, DevOps)

Google Cloud (GCP, Vertex AI, BigQuery, Cloud Run)

Monitoring & Logging: ELK Stack (Elasticsearch, Logstash, Kibana), Grafana, Prometheus

Infrastructure as Code (IaC): Terraform, AWS CDK, Azure Bicep

Version Control & Collaboration: Git, GitHub, GitLab, Bitbucket

CI/CD Pipelines: Build, test, deploy automation, rollback, release management

📱 App Development

Develop mobile and hybrid apps end-to-end:

Android (Java/Kotlin) – UI/UX, activity lifecycle, API integration

Hybrid Frameworks: Ionic, Cordova, React Native

Progressive Web Apps (PWA) – Offline-first, caching, mobile optimization

Firebase Integration: Auth, Firestore, Cloud Messaging

🤖 Artificial Intelligence & Machine Learning

Learn how modern AI systems are built and deployed:

AI Fundamentals: Neural networks, supervised/unsupervised learning

Machine Learning with Python: scikit-learn, TensorFlow, PyTorch

Natural Language Processing (NLP): Transformers, BERT, GPT

Computer Vision: OpenCV, YOLO, Image Classification

AI APIs & Integrations: Google DialogFlow, Azure Cognitive Services, OpenAI API

🧬 Generative AI, RAG & Agentic Systems

Special focus on real-world AI integration and automation:

Generative AI Models (GPT, Claude, Gemini, Llama, Mistral) – Practical implementation

Prompt Engineering – Designing powerful, reusable prompt frameworks

Retrieval-Augmented Generation (RAG) – Hybrid search + generation architectures

Agentic AI Systems – Building autonomous multi-agent workflows (e.g., AutoGPT, CrewAI)

Agentic RAG – Contextual memory, chaining, and reasoning systems

LangChain / LlamaIndex – RAG pipelines, document loaders, embeddings, vector DBs

Vector Databases: Pinecone, Chroma, Weaviate, FAISS

Knowledge Graphs & Context Management – Enterprise data linking with RAG

AI App Deployment: FastAPI + Streamlit + LangServe + Docker

Copilot & AI Tools: GitHub Copilot, ChatGPT API, Code Interpreter, Vertex AI Studio

Google AI Developer Kit (ADK) – Edge AI, TensorFlow Lite, Coral, and model serving

Voice AI & Conversational Design: Dialogflow CX, OpenAI Assistants, ElevenLabs

🔬 Data, Testing & Quality

Database Systems: MySQL, PostgreSQL, MongoDB, Oracle, DB2, Redis

Database Design: ERD, normalization, indexing, performance tuning

Testing Tools: JUnit, Mockito, Selenium, Cypress, Postman

TDD / BDD Practices: Unit, integration, and end-to-end testing

Logging & Monitoring: ELK, Splunk, Prometheus

Performance Optimization: Profiling, caching, concurrency

🧩 Operating Systems & Scripting

Windows / Linux / Ubuntu / Unix Administration

File Systems, Permissions, Networking, Process Management

Shell Scripting / Automation / Log Analysis

System Security and SSH Hardening

🧠 Bonus Topics

Mathematics for Programmers – Logic, combinatorics, probability, graph theory

Game Development Basics: Unity, Phaser.js, HTML5 Canvas

AI Ethics, Data Privacy, Responsible AI Design

Automation Projects & Web Crawling / Scraping: BeautifulSoup, Selenium, Puppeteer

No-Code / Low-Code Integrations: Zapier, Make, AI automations

Mahmood

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Java is one of the most important of all computer programming languages. But learning Java can seem like a daunting task. Not any longer! In this course I will train you well in Java Programming step-by-step. Starting from basis right through the more advanced topics. No prior knowledge is required.

Course outlines:
- Objected Oriented Programming concepts (OOPS)
- Core Java Programming Introduction of Java
- Data types and Variables
- Methods
- Control Flow Statements
- Operators and Expressions
- While and do-while Loops
- Object-oriented Programming
- Objects and classes
- Using Java Objects
- Java Files and I/O
- Interfaces and Abstract Classes
- Inner Classes

Joris

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Python is the fastest growing programming language. Master it and you can solve business and science problems!

If you are an absolute beginner, don't worry, I've got exercises that will help you get up to speed.

About me: I have worked 10 years in financial markets (bond trading and market data). Now I am working as a freelance Python trainer & developer.

Favourite Python packages / frameworks: Pandas, Numpy, Flask, Django, Beautifulsoup, PySpark & Pytest,

Kelly

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Python is a Programming Language widely used with huge capabilities on building projects of many different kinds but the most important advantage is that it is easy to learn and it can be a good start for someone to embrace Computer Science and improve their logical thinking.

Nousha

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Learning to program can be a big challenge, especially if you have to do it alone. There are plenty of videos or documentation to be found, but where do you start? Sometimes you can't see the forest for the trees.

With my experience in programming, mainly in the language C# and framework .NET, and the many years of experience in supervising students, this is an ideal combination in offering guidance in programming.

Albert

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Stephen

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I believe that anyone can learn to program. And with an average rating of 8.5 for my exam training at, among others, lyceo, I have experienced a lot of others doing the same.

Because of the programming minor that I did in addition to my Master's degree in Mathematics, I have seen where the friction is with many students and that often helped them on their way. I can do that because I taught myself to program next to my study Do you need help with a programming assignment, or are you not very good at the theory on your own? Then we start by looking at what you do know or understand, and where things are still unclear. Based on your understanding, we devise a plan of action for your assignment together.

We usually only have an hour together and that flies by. That is why I offer for the entire week (7 days) after our tutoring to help you online, via WhatsApp or Messages (iOS)

See you soon!

Rajitha

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If you want any help with Java or any other programming language, I can assist you with it.

Web Application Development is also my expertise. I can guide you to build a successful web application.

Yoeri

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I can help both with solving concrete problems, and learning Python in general. While I have used many different libraries the past few years, I have specialised knowledge regarding data analysis, visualisation and data science (Numpy, Pandas, Scikitlearn, Seaborn, Scikitlearn ...)

Nadeesha

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Mohamed

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In this course, you will learn how to efficiently package, containerize, and deploy Python applications and microservices using Docker. The course covers fundamental Docker concepts, best practices for structuring Python projects, and strategies for building scalable and portable applications. Through hands-on projects, you will gain practical experience in creating Docker images, managing containers, and orchestrating microservices, enabling seamless deployment across different environments.

Contact me if you want to have more information about the course!

Gilliard

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Greetings! My name is Gil. I'm based in the Den Haag area and am an experienced tutor with a strong background in applied physics holding a bachelor's and soon an master's in the field. I have a deep passion for teaching and helping students succeed.

I offer personalized tutoring in Dutch, English, and Papiamentu for all levels, from VMBO up to university (WO/Bachelor).

Subjects I cover:

* Mathematics A & B

* Physics

* Statistics, Calculus & Algebra (up to WO Bachelor level)

* Chemistry & English (up to VWO level)

* Other subjects are also possible

With over 5 years of experience, I've worked as a lecturer and student coach at TU Delft and Erasmus University, supporting first- and second-year students in courses like Technology Management, Optics, and Electronic Instrumentation.

I focus on building students’ curiosity and confidence by tailoring each session to their learning style and preferred language.

Gergely

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“AI is the future.” You’ve heard it before, but what does it actually mean? Facial recognition, recommendation systems, self-driving cars—it all starts with data, algorithms, and code. The best part? You can learn it too.

Whether you're a curious beginner or someone already dabbling with machine learning, I offer hands-on guidance through the AI jungle. Using libraries like Pandas, Scikit-learn, TensorFlow, and OpenCV, I’ve built projects ranging from eye-tracking systems to classification models. I know how to explain complex concepts in simple terms—and help you build real, working prototypes.

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Tommie

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🐍 Python Programming – Learn by Doing
Course Overview
This class is designed for anyone who wants to learn Python from scratch or strengthen their coding skills. Whether you’re a complete beginner or looking to apply Python in data analysis, automation, or web development, this course will guide you step by step with practical examples and projects.

What You’ll Learn
✅ Python basics: variables, data types, operators, and control flow

✅ Functions and modules: writing reusable, clean code

✅ Working with files and data (CSV, JSON, text)

✅ Object-Oriented Programming (OOP) concepts

✅ Libraries for real-world tasks (e.g., pandas, matplotlib)

✅ Problem-solving strategies and debugging techniques

Teaching Style
Hands-on learning: You’ll write code in every session.

Project-driven: Build mini-projects like calculators, data visualizations, or simple web apps.

Adaptable pace: Lessons tailored to your level and goals (academic, professional, or hobby).

Who Is It For?
Students preparing for exams or computer science courses

Professionals wanting to automate tasks or analyze data

Curious learners who want to start coding as a hobby

Practical Details
📍 Online or in-person (depending on your location)

⏱ Flexible scheduling to fit your availability

🧑‍🏫 Personalized guidance with clear explanations and exercises