Emergency Project Help: Debug, Fix & Deploy Your Web Application Fast

From 31 $ /h

Your project is broken? Deadline approaching? Can't deploy? I help developers and students fix bugs, optimize code, and deploy applications to production.
I Specialize In:

Emergency Debugging: Find and fix errors fast (frontend crashes, backend timeouts, database issues)
Deployment Rescue: Get your app live when nothing works (AWS, Vercel, Netlify)
Performance Optimization: Speed up slow applications (database queries, API responses, bundle size)
CI/CD Setup: Automate your deployment pipeline (GitHub Actions, testing, monitoring)

Common Problems I Solve:

❌ "My app works locally but crashes in production"
❌ "Database queries are too slow"
❌ "Authentication isn't working"
❌ "Can't deploy to AWS / Vercel"
❌ "Getting weird errors I don't understand"
❌ "Payment integration (Stripe) not working"

Technologies I Work With:

Frontend: React, Next.js, TypeScript, Vue, Angular
Backend: Node.js, NestJS, Express, Python (Django, Flask)
Databases: PostgreSQL, MySQL, MongoDB, Redis
Cloud: AWS (EC2, RDS, S3), Vercel, Netlify, Render
DevOps: Docker, CI/CD, GitHub Actions, Nginx

Perfect For:

Students: Fix your project before the deadline
Junior Developers: Debug production issues you can't solve alone
Freelancers: Get unstuck on client projects fast
Startups: Fix and deploy your MVP without hiring a full-time engineer

How It Works:

Live Debugging Session: We fix it together via screen share
Code Review: I show you how to prevent the issue in the future
Documentation: You get a summary of what was fixed and why

Average Resolution Time:

Simple bugs: 1-2 hours
Deployment issues: 2-3 hours
Complex debugging: 3-5 hours

Urgent projects accepted (same-day availability for emergencies).

Location

Online from Netherlands

About Me

I'm Oussama, a Full-Stack Engineer with 3+ years of professional experience building production applications for international clients.

Professional Background:
12+ projects delivered on-time including SaaS platforms, e-commerce sites, and custom dashboards
Reduced deployment time by 88% at DEF TUNISIE through CI/CD automation
Active freelancer serving clients across Europe and North America
Former instructor at Masterclass Denden, where I taught 50+ students (100% project completion rate)

What Makes My Teaching Different:
You learn from real production code, not tutorials
I show you how companies actually build software (debugging, deployment, monitoring)
Focus on practical skills that get you hired or help you ship your project

Technologies I Work With:
Frontend: React, Next.js, TypeScript, Tailwind CSS
Backend: Node.js, NestJS, Express, REST APIs
Databases: PostgreSQL, MongoDB, Redis
DevOps: AWS (EC2, RDS, S3), Docker, CI/CD, GitHub Actions
AI Integration: ChatGPT API, prompt engineering
Integrations: Stripe, OAuth, SendGrid

Who I Help:
Students: Ship your projects with professional standards - deployed live
Career Switchers: Build a portfolio that actually gets you hired
Junior Developers: Learn production practices bootcamps don't teach
Freelancers: Add high-value services (AI integration, DevOps) to your offerings
Entrepreneurs: Build or fix your MVP without hiring a full team

Education

Bachelor's degree in computer science and multimedia
Professional Certificate in DevOps and Software Engineering
MicroBachelors® program in Full Stack application development

Experience / Qualifications

✓ 3+ years professional software development
✓ 12+ projects delivered on-time for international clients
✓ 88% deployment time reduction at DEF TUNISIE through CI/CD automation
✓ Former Instructor at Masterclass Denden

Age

Children (7-12 years old)

Teenagers (13-17 years old)

Adults (18-64 years old)

Seniors (65+ years old)

Student level

Beginner

Intermediate

Advanced

Duration

60 minutes

The class is taught in

French

English

Arabic

Skills

Database

Web development

Computer programming

Reviews

Availability of a typical week

(GMT -05:00)

Chicago

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Professional Full-Stack Web Development: React, Node.js, AWS & Production Deployment

33 $ /h

Learn to build production-ready web applications from a professional engineer with 3+ years of experience delivering real client projects

What You'll Master:
Frontend: React, Next.js, TypeScript, responsive design, state management
Backend: Node.js, NestJS, REST APIs, authentication (JWT, OAuth), security best practices
Databases: PostgreSQL, MongoDB - proper schema design, queries, optimization
DevOps: Deploy to AWS (EC2, RDS, S3), Docker, CI/CD with GitHub Actions
Integrations: Stripe payments, email automation, file uploads

What Makes This Different:
Work on YOUR project (PFE, portfolio, startup MVP) - not generic tutorials
Learn production debugging - how to fix real errors, not just write code
Get your app deployed LIVE with proper CI/CD and monitoring
GitHub repo ready to show employers with professional commit history

Perfect For:
Students: Ship your projects with professional standards (authentication, deployment, documentation)
Career Switchers: Build 2-3 portfolio projects that get you hired
Junior Devs: Learn what companies actually need (debugging, testing, deployment automation)

What You'll Build:
Full-stack application deployed to AWS
User authentication system (login, OAuth, password reset)
Admin dashboard with real-time data
Payment integration with Stripe
Complete with CI/CD pipeline and monitoring

Bonus: I'll review your resume and help position you for remote developer roles.

Python Programming & AI Integration for Web Developers: ChatGPT API, Prompt Engineering & AI Features

31 $ /h

Learn to add AI features to your applications using ChatGPT API. Taught by a Full-Stack Engineer who's integrated AI into real client projects.

What You'll Learn:
ChatGPT API Integration: Add AI chat, content generation, or text analysis to any web app
Prompt Engineering: Write effective prompts that give consistent, quality results
Production Implementation: Rate limiting, cost management, error handling, security
Real-World Deployment: Deploy AI features to AWS with proper monitoring and logging

Technologies:
OpenAI API (ChatGPT-4)
React/Next.js frontend integration
Node.js/NestJS backend
Secure API key management
Cost optimization (don't waste money on API calls)

Perfect For:
Developers: Add AI to your portfolio (instant differentiation from other candidates)
Freelancers: Offer AI integration services
Students: Build an AI-powered projects that stands out
Entrepreneurs: Add AI features to your product without hiring an AI engineer

What We'll Build:
AI chatbot for your website (customer support, FAQ assistant)
Content generation tool (blog posts, product descriptions, social media)
Text analysis features (summarization, sentiment, keyword extraction)
Custom AI assistant for your specific use case

Real Examples:

E-commerce: AI product description generator
Real estate: AI property listing writer
Marketing: AI social media content creator
Education: AI study assistant

What's Included:
Working code you can deploy immediately
Cost management strategies (API calls can get expensive!)
Error handling and fallback strategies
Production deployment checklist

No AI experience needed - just basic JavaScript/React knowledge.

4.85

(13)

Engineer and senior professor of engineering sciences provides support courses in analog and digital electronics at all levels, engineering schools. having a scientific and technical knowledge, five years of experience in the field of teaching, teaching and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they have difficulties. for more info please contact me

Negar

4.85

(13)

Are you interested in learning programming, Artificial Intelligence, or Machine Learning but don't know where to start? I offer personalized lessons designed for beginners, students, and professionals who want to build strong practical skills in computer science and AI.

In this course, you will learn:

1. Programming & Algorithms
a) Programming fundamentals and problem-solving techniques
b) Algorithm design and data structures
c) Writing efficient and clean code

2. Python Programming (Beginner to Advanced)
a) Python basics, object-oriented programming, and advanced concepts
b) Using Python for real-world applications in:
I) Machine Learning
II) Computer Vision
III) Robotics
IV) Data Science
c) Scientific Python (NumPy, Pandas, Matplotlib)

3. Artificial Intelligence & Machine Learning
a) Core AI concepts and algorithms
b) Deep Learning fundamentals
c) Practical projects using modern AI tools and frameworks

Lessons are adapted to your background and goals, whether you are starting from zero, preparing for university courses, or looking to apply AI in your own projects.

Feel free to contact me if you have any questions. I look forward to helping you explore the world of AI!

Adam

4.85

(13)

doctoral student in engineering sciences provides support courses in analog and digital electronics at any DEUG level and engineering schools. having scientific and technical knowledge, three years of experience in the field of teaching, pedagogy and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they are having difficulty. for more info please contact me

Zakaria

4.85

(13)

* This digital training aims to introduce you to the Scratch tool and through the game world, and gradually, to discover programming concepts such as loops, conditions or variables. It is aimed at anyone who is new to Scratch and who wants to create games and animations.

* Learning programming will allow students to develop their skills and will certainly allow them to meet the expectations of the future working world and emerging careers.

* In addition, learning programming allows the development of algebraic, algorithmic and computational thinking. Programming also helps to improve and develop students' sequencing ability, as well as their communication skills. Thus, there are several advantages to teaching programming, but the important thing is to remember that this learning teaches students that digital is not only for entertainment, but that it is possible to become creators. active and creative content.

Gaëlle

4.85

(13)

While adults are still debating whether kids should use AI, they are already using it.
The question isn't "should they?" it's "how do we do it intelligently?"

In this course, your child will discover:
✓ What AI actually is: not magic, not mystery. How machines think, what they can do, what they can't
✓ How ChatGPT really works: not just "ask a question and get an answer," but why it responds that way, where it fails, when to trust it
✓ What LLMs are (Large Language Models): in language they understand, not tech jargon
✓ Create with AI: custom avatars, interactive stories, real projects using real tools
✓ Think critically about AI: Bias, privacy, creativity. What does AI do better than humans? What can't it do?
✓ Real-world applications: How AI transforms medicine, education, art, gaming, everyday life

Why this is different:
Most AI courses for kids teach "here's the tool, use it." I teach how to think about AI.
Your child will learn to see AI not as black magic or a solution to everything, but as a powerful tool with real limits.
And, more importantly: that they can control how they use it.

What they take home:
Real projects they created (custom avatar, interactive app, analysis of a real AI case study). A genuine understanding of how it works. And the ability to use AI responsibly and creatively.

Format: Online | 60–90 min sessions | Flexible, adapted to their age and pace

For curious kids asking "How does ChatGPT actually know things?"

Salah

4.85

(13)

Master Python with Personalized Courses

Discover the art of programming with Python courses tailor-made to meet your specific needs. Whether you are a beginner, intermediate or professional, my lessons are suitable for all levels.

Why Choose My Courses?

Personalized Teaching Approach: Each course is tailored to your skill level and individual goals.

Practical Experience: Learn by doing with real-world projects that build your understanding and skills.

Ongoing Support: Get unlimited email support for any questions you have between sessions.

As a Python expert, I have a passion for teaching and sharing my knowledge. My goal is to guide you effectively in your learning journey.

Book Your First Lesson:

Start your journey to Python mastery now by booking your first lesson. Whether you aspire to enter the development field or hone your existing skills, these courses are designed for you.

Hassane

4.85

(13)

Description:
This course is ideal for beginners or intermediate learners who want to learn programming using languages like C#, Java, or Python. With a step-by-step approach, you'll be guided from basic algorithms to object-oriented programming.

Goals :

Introduction to algorithms and their implementation.
Master the basics of C#, Java, and Python languages.
Understand the concepts of classes, objects, and error management.
Course methods and format:

Video lessons: Clear explanations and practical exercises.
Flexibility: Personalized support to meet your expectations.
For who ?
Students or professionals starting out in programming, or preparing for exams.

Baia

4.85

(13)

I teach Python specifically for finance and data applications - the kind used in economics, business analytics, and quantitative programs. This isn't a general "learn to code" course; it's built around real financial data, benchmarking, and the workflows you'll actually use in coursework or early career work.

Topics include:
Python fundamentals through a finance lens (data structures, functions, control flow).
Working with financial data and datasets.
Performance benchmarking and writing efficient code.
Applying concepts from Hilpisch's Python for Finance.

Hayat

4.85

(13)

This course is designed for anyone interested in learning data science using Python. It provides a hands-on introduction to fundamental data analysis tools such as NumPy, pandas, matplotlib, and seaborn. You'll learn how to manipulate datasets, create visualizations, and lay the foundations for statistical analysis and machine learning.

The course combines theory and practical exercises for effective, practical progress. No prior programming experience is necessary: we'll start with the basics to build solid, usable skills quickly.

Yomna

4.85

(13)

This course is designed to introduce students aged 7 to 16 to the world of programming through two of the most widely used and industry-relevant languages: C++ and Python.

The class provides a structured, age-appropriate pathway into programming, whether the student is a complete beginner or already exploring coding through platforms like Scratch or Code.org. Emphasis is placed on understanding logic, building problem-solving skills, and writing real code in a supportive, project-based environment.

Taught by an engineering student with hands-on experience in both C++ and Python, this course empowers students to explore the power of code and build a strong foundation in computational thinking — essential for future studies in engineering, robotics, AI, or game development.

Mohamed

4.85

(13)

This fun and interactive course introduces kids and teens to the fundamentals of coding using Scratch, a visual programming language developed by MIT. Students will learn to create games, animations, and interactive stories while developing problem-solving, logical thinking, and creativity skills—all in a playful, drag-and-drop environment!
Who Should Join?
✔ Kids & teens curious about coding and game design
✔ Young learners who enjoy storytelling, art, or technology
✔ Future coders looking for a fun introduction to programming

Ali

4.85

(13)

I offer one-to-one Programming tuition in Python, C, and C++, for GCSE Computer Science, A-Level Computing, and university students studying engineering, computer science, or related subjects. Lessons are available online or in person around Birmingham.

What I cover:

Python for beginners and intermediate learners
C and C++ programming
GCSE and A-Level Computer Science (all exam boards)
University coursework support, debugging help, and project guidance
Core concepts: variables, loops, functions, data structures, object-oriented programming, file handling, basic algorithms

How I teach:
I start by understanding exactly where you are — whether that's "I've never coded before" or "I'm stuck on a specific assignment." Then I build lessons around small, practical examples you can actually run and modify yourself. I'm patient with errors (everyone gets them), and I make sure you understand the why behind the code, not just how to copy it. For university students, I can also help with debugging, code reviews, and explaining tricky concepts in plain English.
If you or your child is preparing for exams, working on coursework, or just wants to finally feel comfortable with coding, I'd love to help.

Ammar

4.85

(13)

A- TOPICS YOU CAN EXPLORE AND MASTER:
1- PYTHON FOUNDATIONS
• Variables, data types, operators, conditional structures, loops, functions, modules, files, exceptions, and object-oriented programming
• Lists, tuples, dictionaries, sets, comprehensions, debugging, and writing clear, reusable, well-structured code
• Jupyter Notebook, Anaconda, Visual Studio Code, virtual environments, and package management

2 — PROGRAMMING, ALGORITHMS, AND COMPUTER SCIENCE FOUNDATIONS
• Algorithmic thinking, problem decomposition, pseudocode, flowcharts, procedural programming, object-oriented programming, recursion, and modular program design
• Fundamental data structures including arrays, lists, stacks, queues, dictionaries/hash tables, sets, trees, graphs, and their appropriate use
• Searching, sorting, traversal, algorithm efficiency, computational complexity, Big-O notation, debugging, testing, code organization, and problem-solving strategies
• Practical programming exercises ranging from beginner problems to university-level algorithmic and computational challenges

3- DATA PREPARATION AND EXPLORATION
• NumPy and pandas for importing, cleaning, transforming, filtering, grouping, reshaping, and merging data
• Missing values, duplicates, outliers, inconsistent formats, data leakage, and data-quality validation
• Exploratory data analysis using descriptive statistics, Matplotlib, Seaborn, and graphical interpretation

4- MATHEMATICAL FOUNDATIONS
• Linear algebra, vectors, matrices, derivatives, optimization, probability, and statistics
• Loss functions, gradients, distance measures, regularization, likelihood, and model complexity
• Mathematical concepts are explained according to the learner’s level and the requirements of the selected algorithms

5- SUPERVISED MACHINE LEARNING
• Linear and polynomial regression, logistic regression, and regularized models
• k-nearest neighbours, decision trees, random forests, gradient boosting, support vector machines, and Naive Bayes classifiers
• Classification, regression, model assumptions, decision boundaries, feature importance, and interpretation of results

6- UNSUPERVISED LEARNING
• Clustering using k-means, hierarchical clustering, and density-based methods
• Principal component analysis, dimensionality reduction, anomaly detection, and pattern or structure discovery
• Method selection, evaluation of data structure, and interpretation of results without predefined labels

7- MODEL EVALUATION AND IMPROVEMENT
• Training, validation, and test sets; cross-validation; hyperparameter optimization
• Accuracy, precision, recall, specificity, F1 score, ROC–AUC, confusion matrices, MAE, MSE, RMSE, and R2
• Underfitting, overfitting, bias–variance trade-off, class imbalance, feature engineering, feature selection, scaling, and regularization

8- DEEP LEARNING
• Neural-network foundations, activation functions, forward propagation, backpropagation, and gradient descent
• Multilayer perceptrons, convolutional neural networks, recurrent neural networks, and Transformer foundations
• TensorFlow, Keras, or PyTorch depending on the learner’s project and working environment

9- ARTIFICIAL INTELLIGENCE APPLICATIONS
• Natural language processing, text classification, embeddings, sentiment analysis, and foundations of language models
• Computer vision, image classification, fundamental principles of object detection, and image preprocessing
• Recommendation systems, forecasting, anomaly detection, intelligent automation, and decision-support applications

10- GENERATIVE AI AND LARGE LANGUAGE MODELS
• Transformer architecture, tokens, embeddings, attention mechanisms, prompt engineering, Retrieval-Augmented Generation (RAG), and model evaluation
• Use of artificial-intelligence APIs, vector databases, document-retrieval systems, and structured AI-enabled workflows when relevant
• Reliability, hallucinations, bias, privacy, responsible use, and appropriate human validation

11- TOOLS AND LIBRARIES
• Python, NumPy, pandas, Matplotlib, Seaborn, scikit-learn, SciPy, Statsmodels, TensorFlow, Keras, and PyTorch
• Jupyter Notebook, Anaconda, Visual Studio Code, Git, GitHub, SQL, Excel, and Power BI when useful to the project
• Additional libraries may be introduced depending on the selected specialization and dataset

12- PROJECTS, RESEARCH, AND INTERVIEW PREPARATION
• Complete projects covering data preparation, model development, evaluation, interpretation, and presentation of results
• University assignments, dissertations, theses, research projects, portfolio projects, technical interviews, and professional applications
• Code review, debugging, documentation, reproducibility, model comparison, and communication of results

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
B- PERSONALIZED TUTORING: LEARNING HOW TO REASON
Machine learning and artificial intelligence become much more accessible when mathematics, algorithms, Python code, data, and real-world applications are clearly connected.

My lessons help you move beyond simply copying code or using models as “black boxes.” You will learn how to define the problem correctly, prepare the data, select an appropriate algorithm, understand how it works, train and evaluate the model, diagnose errors, improve performance, and interpret results rigorously and responsibly.

Each lesson is personalized according to your current level, mathematical background, programming experience, dataset, university work, research project, interview preparation, or professional objective. We begin by identifying your existing knowledge, software environment, expected outcomes, and main conceptual or technical difficulties. We then establish a structured learning plan.

The first lesson combines a discussion of your background, objectives, and tutoring needs; an initial assessment of your current knowledge; personalized planning and organization of future sessions; and a short trial lesson to determine the most effective learning approach.

A typical session may include conceptual explanation, development of mathematical intuition, live coding, guided implementation, model evaluation, technical problem solving, and a concise summary of the next steps.

You may work with your own dataset, university assignment, research project, or professional problem, provided that confidential information is handled appropriately. I can also provide structured examples and datasets suited to your level.

My goal is not simply to help you run an algorithm. It is to help you understand why it is appropriate, how it learns from data, how to evaluate it correctly, why it may fail, and how to build a reliable, interpretable, and scientifically rigorous solution.

Abdelmalek

4.85

(13)

This hands-on training pathway is designed to help students kickstart any project, specifically tailored for OT labs and industrial applications. Starting from absolute scratch, students will build a strong foundation in Python programming through practical, industry-relevant concepts.

Curriculum Outline: |
01 - Python Environment Setup & Basics |
02 - Python Variables, Numbers, Bytes & Hex |
03 - Control Flow Logic Functions |
04 - Data Structures (Lists, Tuples, Dictionaries & Sets) |
05 - String Formatting, Comprehensions & Exception Handling |
06 - File IO, Pathlib & Context Managers |
07 - Object-Oriented Programming (Classes & OOP) |
08 - Standard Library, Modules & Networking Basics |

Assessment & Evaluation:
Students will take a mini-test after the completion of each module. Additionally, an Audit & Performance Evaluation report will be sent following the tests.
Duration:
5 days to 15 days (depending on the pace of the cohort)

Jude

4.85

(13)

My lessons are designed to take you from simply following code to genuinely understanding how data science works.

We can cover the complete data science process, including data cleaning, exploratory data analysis, feature engineering, visualisation, statistics, machine learning, model evaluation and communicating results.

Depending on your goals, lessons can include:

Python, pandas, NumPy and scikit-learn
Data cleaning and exploratory analysis
Regression and classification
Decision trees, random forests and boosting
Clustering and dimensionality reduction
Cross-validation and model evaluation
Feature engineering and model interpretation
Neural networks and deep learning foundations
Bayesian modelling and PyMC
Portfolio and interview preparation
Support understanding university modules and projects

I use diagrams, analogies and practical demonstrations to make difficult ideas easier to understand. We will normally begin with an intuitive explanation, look at the underlying logic or mathematics, and then implement the concept in Python.

Lessons are personalised around your level. Complete beginners receive a structured learning path, while experienced students can focus on advanced topics, project guidance, debugging or interview preparation.

You will be encouraged to explain ideas back to me, interpret results and make your own modelling decisions. My goal is not only to help you produce working code, but to help you become an independent and confident data scientist.