Accelerate Your Machine Learning Skills: Learn from a PhD graduate, academically trained with professional and academic experience

From 207 C$ /h

SERVICES
I can offer my assistance with Data Analysis, Data Science, Quantitative Methods, Analysis, Statistical Modelling, Forecast, Regression, Coding, Python, Matlab, Excel statistical software and packages such as Stata, R and Database languages such as SQL, Oracle, MySql and other Business-related subjects (with coding and programming if you are interested in it).
I understand that there are different kinds of learning methods, so as long as you can find your style and the appropriate method, I believe that you can get twice the result with half the effort. I have been told to be good at breaking down complex statistical and modelling concepts, explaining them in diagrams, and also relating them to their uses in our daily lives. I can help you to understand statistics, econometrics, linear regression, forecast modelling, statistical modelling, quantitative methods, as well as introducing you to the fast-growing field of Data Analysis and Data Science. I can teach how to use Python, Matlab, Stata, R, Sas, R, Excel, SQL, Oracle, MySql and many more.

- Statistics
- Machine Learning
- Deep Learning
- Probability
- Linear Regression
- Statistical Modelling
- Analysis
- Data Analysis/Science
- Modelling
- Forecasting model
- Time Series Analysis
- Quantitative Methods
- Python
- Matlab
- Stata
- R
- Sas
- Excel

EXPERIENCE AND EDUCATION
- PhD graduate in Finance, with 5 years of research experience and scientific contribution in the field of empirical asset pricing with focus on equity factor models, machine learning for asset pricing, regime switching models, sentiment analysis, and portfolio construction
- Freelance tutor and consultant in Finance, Data Science, Python, Statistics, and Econometrics for 3 years with 1500+ hours delivered to 150+ students and customers internationally
- Former financial analyst with 4 years of experience in design and realization of prototypes of several financial algorithms of a proprietary software for portfolio management, analysis, and consulting
- Experienced in written and oral communication to various audiences, from academic students to financial industry leaders and professionals through reviewing, editing, teaching, consulting, and oral presentations
- Former University Teaching Assistant, strong analytical background with extensive classroom and online teaching experience, MSc in Quantitative Finance, Bachelor of Science in Economics and Finance
- Excellent material available including slides, videos, tutorials and reading material. Extensive experience in research methods and software including Python, Jupyter notebook, Matlab, Sas, Stata, R, SQl/Oracle and Excel.
- I thoroughly enjoy helping others, as my patience and friendly nature makes it easier to be in an educational environment.
- I have learnt to adapt to different needs and learning styles according to the student, in order to optimise their success in turning their weaknesses into strengths.
- I'm patient, friendly and understanding. I am proficient in research and development and it’s my day to day work. I am a photography enthusiast and an insatiable learner.

GREETINGS
My goal is also to inspire further study that will lead to an interesting and successful career. If you need further information about myself or my services, please do not hesitate to contact me. Feel free to send me a message and I'd be happy to give you an informal consultation.

Thank you for looking at my profile and hope to hear from you soon,
Andrea

Location

Online from Hong Kong

About Me

EXPERIENCE AND EDUCATION
- PhD graduate, current research focuses on Machine Learning for Asset Pricing (Finance)
-2500+ hours of tutoring and consulting to 300+ students/clients
- Financial Management University Teaching Assistant.
- Academically trained to teach.
- Strong Analytical background with extensive classroom and online teaching experience.
- MSc in Quantitative Finance, Bachelor of Science in Economics and Finance.
- 4 years of experience as a Financial Analyst in a Fintech company.
- For the last 2.5 years I have tutored, in Hong Kong and online, Statistics, Mathematics, Data Analysis and Italian language, both with private face-to-face tutoring as well as small groups, with students ranging from 5 years old to adult learners.
- Excellent material available including slides, videos, tutorials and reading material. Extensive experience in research methods and software including Python, Jupyter notebook, Matlab, Sas, Stata, R, Sql/Oracle and Excel.
- I thoroughly enjoy helping others, as my patience and friendly nature makes it easier to be in an educational environment.
- I have learnt to adapt to different needs and learning styles according to the student, in order to optimise their success in turning their weaknesses into strengths.
- Since my academic background is Economics and Finance, I would be more than happy to assist you with substantive work too in that field.
- I'm patient, friendly and understanding. I am proficient in research and development and it’s my day to day work. I am a photography enthusiast and an insatiable learner.

I can offer my assistance with Finance, Financial Management, Corporate Finance, Investment and related subjects (with coding and programming if you are interested in it).

I can also offer my assistance with Statistics, Mathematics, Econometrics and Data Analysis/Science and other Business-related subjects (again with coding and programming if you are interested in it).

I am at your disposal for any help/assistance/consultation you would need for the writing of your thesis/dissertation/assignment/project/presentations/essay in Business, Management, Finance, Economics, Data Analysis, Data Science, Statistics and more. I can provide feedback post-reviewing as well as prior to editing should the person want to discuss how much editing/preferred form of editing needs to be described. Provide a valuable second set of eyes to your work. I also help with university courses.

Education

- PhD Graduate, current research focused in Machine Learning for Asset Pricing (Finance)
- MSc in Quantitative Finance, Bachelor of Science in Economics and Finance

Experience / Qualifications

- 6 years PhD researcher, 3 years academic assistant, 4 years financial analyst
- for the last 2.5 years I have tutored, in Hong Kong and online, Statistics, Mathematics, Data Analysis, Finance, CQF, both with private face-to-face tutoring as well as small groups

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

English

Italian

Skills

Computer science

Availability of a typical week

(GMT -04:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

PhD Finance, Financial Management, Business, Econometrics, Economics, Investments (+coding) tutor

196 C$ /h

SERVICES
I can offer my assistance with Finance, Financial Management, Corporate Finance, Investment and related subjects (with coding and programming if you are interested in it).
I understand that there are different kinds of learning methods, so as long as you can find your style and the appropriate method, I believe that you can get twice the result with half the effort. I have been told to be good at breaking down complex scientific concepts, explaining them in diagrams, and also relating them to their uses in our daily lives. I can help you to understand Finance, Economics, Econometrics, Investments and Business-related subjects (Financial Management, Financial Analysis, Investments, Portfolio Theory and Management, Budgeting, Asset Pricing, Forecasting Models and many more) as well as introducing you to the fast-growing field of Data Analysis and Data Science.

- Asset Pricing
- Bond Pricing & Valuation
- Capital Allocation
- Capital Asset Pricing Models (CAPM)
- Corporate Finance
- Derivatives
- Econometrics
- Economics
- Game Theory
- Finance
- Financial Economic Analysis
- Financial Economics
- Financial Management
- Financial Market
- Financial Planning
- Financial Statement
- Forecasting Financial Series and Data
- Fundamental Financial Concepts
- International Finance
- Investment management
- Macroeconomic
- Mergers & Acquisitions
- Microeconomic
- Portfolio Theory and Management
- Pricing Model Theory
- Quantitative Methods
- Research Methodology
- Risk Returns

EXPERIENCE AND EDUCATION
- PhD graduate in Finance, with 5 years of research experience and scientific contribution in the field of empirical asset pricing with focus on equity factor models, machine learning for asset pricing, regime switching models, sentiment analysis, and portfolio construction
- Freelance tutor and consultant in Finance, Data Science, Python, Statistics, and Econometrics for 3 years with 1500+ hours delivered to 150+ students and customers internationally
- Former financial analyst with 4 years of experience in design and realization of prototypes of several financial algorithms of a proprietary software for portfolio management, analysis, and consulting
- Experienced in written and oral communication to various audiences, from academic students to financial industry leaders and professionals through reviewing, editing, teaching, consulting, and oral presentations
- Former University Teaching Assistant, strong analytical background with extensive classroom and online teaching experience, MSc in Quantitative Finance, Bachelor of Science in Economics and Finance
- Excellent material available including slides, videos, tutorials and reading material. Extensive experience in research methods and software including Python, Jupyter notebook, Matlab, Sas, Stata, R, SQl/Oracle and Excel.
- I thoroughly enjoy helping others, as my patience and friendly nature makes it easier to be in an educational environment.
- I have learnt to adapt to different needs and learning styles according to the student, in order to optimise their success in turning their weaknesses into strengths.
- I'm patient, friendly and understanding. I am proficient in research and development and it’s my day to day work. I am a photography enthusiast and an insatiable learner.

KEYWORDS
| Data Analysis | Derivatives | Econometrics | Economics | Excel | Finance | Corporate Finance | Financial Management | Financial Market | Financial Statement | Investment management | Macroeconomic | Matlab | Microeconomic | Pandas | Portfolio Theory and Management | Pricing Model Theory | Programming | Python | Quantitative Methods | Research Methodology | Securities Analysis | SQL | Statistical Modelling | Statistics | Time Value of Money | Valuation |

GREETINGS
If you need further information about myself or my services, please do not hesitate to contact me. Feel free to send me a message and I'd be happy to give you an informal consultation.

Thank you for looking at my profile and hope to hear from you soon,
Andrea

PhD Economics, Econometrics Microeconomics, Macroeconomics (+coding) tutor

207 C$ /h

SERVICES
I can offer my assistance with Economics, Econometrics, Microeconomics, Macroeconomics and related subjects (with coding and programming if you are interested in it).
I understand that there are different kinds of learning methods, so as long as you can find your style and the appropriate method, I believe that you can get twice the result with half the effort. I have been told to be good at breaking down complex scientific concepts, explaining them in diagrams, and also relating them to their uses in our daily lives. I can help you to understand Finance, Economics, Econometrics, Investments and Business-related subjects (Financial Management, Financial Analysis, Investments, Portfolio Theory and Management, Budgeting, Asset Pricing, Forecasting Models and many more) as well as introducing you to the fast-growing field of Data Analysis and Data Science.

- Macroeconomic
- Microeconomics
- International Economics
- Econometrics
- General Economics
- Economics
- Forecasting Financial Series and Data
- Fundamental Financial Concepts
- International Finance
- Portfolio Theory and Management
- Quantitative Methods
- Economic Methodology
- Economic Theory
- Political Economy
- Mathematical Economics

EXPERIENCE AND EDUCATION
- PhD graduate in Finance, with 5 years of research experience and scientific contribution in the field of empirical asset pricing with focus on equity factor models, machine learning for asset pricing, regime switching models, sentiment analysis, and portfolio construction
- Freelance tutor and consultant in Finance, Data Science, Python, Statistics, and Econometrics for 3 years with 1500+ hours delivered to 150+ students and customers internationally
- Former financial analyst with 4 years of experience in design and realization of prototypes of several financial algorithms of a proprietary software for portfolio management, analysis, and consulting
- Experienced in written and oral communication to various audiences, from academic students to financial industry leaders and professionals through reviewing, editing, teaching, consulting, and oral presentations
- Former University Teaching Assistant, strong analytical background with extensive classroom and online teaching experience, MSc in Quantitative Finance, Bachelor of Science in Economics and Finance
- Excellent material available including slides, videos, tutorials and reading material. Extensive experience in research methods and software including Python, Jupyter notebook, Matlab, Sas, Stata, R, SQl/Oracle and Excel.
- I thoroughly enjoy helping others, as my patience and friendly nature makes it easier to be in an educational environment.
- I have learnt to adapt to different needs and learning styles according to the student, in order to optimise their success in turning their weaknesses into strengths.
- I'm patient, friendly and understanding. I am proficient in research and development and it’s my day to day work. I am a photography enthusiast and an insatiable learner.

KEYWORDS
| Data Analysis | Derivatives | Econometrics | Economics | Excel | Finance | Corporate Finance | Financial Management | Financial Market | Financial Statement | Investment management | Macroeconomic | Matlab | Microeconomic | Pandas | Portfolio Theory and Management | Pricing Model Theory | Programming | Python | Quantitative Methods | Research Methodology | Securities Analysis | SQL | Statistical Modelling | Statistics | Time Value of Money | Valuation |

GREETINGS
If you need further information about myself or my services, please do not hesitate to contact me. Feel free to send me a message

Thank you for looking at my profile and hope to hear from you soon,
Andrea

Robert

4.74

(27)

As a Franco-Belgian management teacher, I give Excel lessons with passion!
Whether remotely or face-to-face, I offer many examples and exercises to accompany you.
I travel without problem throughout the region of Brussels and its surroundings, for lessons of at least 2 hours. For France, courses are only given remotely.

Here are some key words that will be covered in my classes:
Scenario analysis, Year, Rounding, Today, Bdnb, Bdnbval, Bdsum, Search, Column, Copy/paste in values, Copy/paste with transposition, Consolidation, Date, Datedif, Determat, Dollar, Right, Righterg, Equiv, Esterror, Estna, Frequency, Filter (simple and advanced), Format of cells, Left, Large.Value, Printing of documents, Index, Indirect, Inversemat, Day, Weekday, Line, Matrix, Max, Maxa, Max.Si, Min , Mina, Mina.If, Formatting of cells and ranges, Month, Average, Average.If, Nb, Nb.If, Nbval, Naming of cells and ranges, No, Small.value, Product, Productmat, Protection of cells, Lookup (Lookup), Lookupv (VLookup), Lookuph (HLookup), If (If), If.Not.Disp, If.Conditions, Iferror, Sum, Sumproduct, Sum.If, Sum.If.Set, Substitute , Pivot tables, Sorting, Cell locking

Do not hesitate to contact me to organize your lessons according to your needs and availability. Together, we will develop your Excel skills in an efficient and personalized way.

Khalil

4.74

(27)

If you’ve ever felt that science and math are difficult, it’s probably because no one showed you how to think like a problem solver.
In my classes, you’ll learn not just formulas or code but how to truly understand concepts, apply them, and build strong logical intuition.

I teach:
• 🔢 Mathematics: From algebra and calculus to applied problem-solving for real-world use.
• 💻 Computer Science: Coding fundamentals (Python, C++), algorithms, and logical thinking for beginners and intermediate learners.
• ⚛️ Physics: Mechanics, thermodynamics, and practical examples that make abstract ideas simple and visual.

As a Software Engineer and Master’s student in Engineering at Nagoya University, I bring both academic knowledge and hands-on experience from real projects. My teaching approach is interactive, visual, and deeply focused on understanding over memorization.

Let’s turn complex problems into clear, step-by-step insights — and make learning something you genuinely enjoy.

Antonin

4.74

(27)

Need a catch-up, tutoring, private lessons or help with homework in mathematics? In computer science ? In logic?
I'm here for you!
I offer you a personalized approach; because there is no one method that works for everyone, I adapt to the needs and requests of each student (and their parents). The first hour of class will be used to define the student's needs, deadlines and strengths.
My courses are aimed at secondary school students of all levels, higher education students and anyone wishing to refresh or strengthen their knowledge of mathematics and computer science. I have been helping friends and acquaintances on a voluntary basis for a long time in the success of their studies and I hope to be able to put this experience to the benefit of your success :)

Mouad

4.74

(27)

⭐⭐⭐⭐⭐

👨‍🎓 With 5 years of experience in distance learning, I am a mathematics teacher, specializing in support courses and private lessons.
I also teach physics and chemistry as well as science subjects in general.

I hold a Master's degree in Operations Research (Applied Mathematics) and I have been teaching private lessons for over 5 years, mainly mathematics for middle and high school levels.

✏ I have taught students from public, private, French Program (Mission), Belgian, Swiss, Spanish Program (students from the Spanish school who are French or English speaking), American Program...
In short, all French or English programs.

✏ I accompany students from A to Z, in all stages of their learning with a simple, new generation and effective methodology: Course explanation, course summary, deepening application exercises etc...

✏ I prepare for exams and competitions

✏ I help with homework.

✏ My students have all evolved in an extraordinary way and have all achieved their goals. 16, 17, 18, 19 out of 20.

Sessions usually take place as follows:

1️⃣ The first sessions are mainly intended to gauge the level of the student in order to highlight the shortcomings observed.

2️⃣ Then comes the establishment of a plan to fill the gaps: Number of hours of work required, The parts of the lessons to focus on, Several training and development exercises...

3️⃣ We make sure to do all of this while staying up to date with the student's class teacher.

4️⃣ I then provide exams similar to what is likely to be asked in class.

5️⃣ I draw up a report on demand, usually monthly, in order to keep parents informed about their child's level throughout the course.

I also adapt my methodology according to the needs of each student, so everyone has a personalized working method adapted to their needs!

I also do crash courses for those who are preparing for the start of the school year so that they start the year strong 💪 and know the program in advance. 🧠

💭 If you have any questions, don't hesitate to contact me ;)

Reza

4.74

(27)

You will learn Systematic Reasoning & Logical Thinking which is a requirement for entering Computer Science program in many universities.
The book “Delftse Foundations of Computation” especially its second chapter will be the main source of our lesson, but other more in-depth books will be also covered if you want to improve even further on logical thinking.
The topics in our lesson include:
• Propositional Logic: Logical operators; Precedence rules; Logical equivalence; Implications in English; Exclusive or; Universal operators; Classifying propositions
• Boolean Algebra: Substitution laws
• Logic Circuits: Logic gates; Combining gates to create circuits; From circuits to propositions; Disjunctive Normal Form; Binary addition.
• Predicate Logic: Predicates; Quantifiers; Tarski’s world and formal structures;
• Deduction: Valid arguments and proofs; Proofs in predicate logic

If you have any additional questions before starting a class, please feel free to ask me. I am here to assist! :)

Amine

4.74

(27)

Discover programming lessons suitable for children! With a fun and educational approach, my lessons allow young minds to dive into the fascinating world of programming. Provide your children with an enriching learning opportunity in a fun and stimulating environment.

Florian

4.74

(27)

Experienced and patient teacher of logic for computer science.

I have taught logic, formal languages and automata theory to undergraduates for six years. My tutoring is adapted to the student's level and goals. Whether you need to learn logic for your studies, or you would simply like to know more about the subject, I will be more than happy to help you improve your understanding and skills.

Logic
The sciences presuppose a certain standard of rationality. An ability to distinguish between correct reasoning and claims that do not follow from the assumptions. In this class we study the basic principles of logic and apply mathematical techniques to the study thereof.
Topics include:
Propositional and Predicate Logic
Syntax and semantics
Natural deduction
Semantic tableaux
Correctness and soundness
Completeness

Formal languages and automata
A formal language is an abstraction of general characteristics of programming languages. Such a languages consists of a set of symbols together with some rules to determine whether a string made up out of those symbols is a member of the language.

Topics include:
Regular languages, context-free languages
Finite automata, pushdown automata, Turing machines
Regular expressions
Regular grammar, context-sensitive grammar
Pumping lemmas for regular and context-free languages

Baia

4.74

(27)

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.

Amr

4.74

(27)

In today's rapidly evolving technological landscape, **Python programming** has emerged as one of the most **critical skill sets** for professionals across industries. With applications spanning web development, data science, artificial intelligence, automation, and more, Python continues to dominate as the **language of choice** for developers and organizations worldwide. This proposal outlines a comprehensive Python course designed and delivered by **Amr**, a developer and instructor with over **20 years of experience** in the field. The course combines fundamental programming concepts with practical, real-world applications, ensuring students gain not just theoretical knowledge but **marketable skills** that align with current industry demands. By leveraging cutting-edge teaching methodologies and extensive professional experience, this course offers an unparalleled learning opportunity for aspiring programmers and experienced developers alike.

## 1 Introduction to Python Programming

Python has established itself as a **powerhouse programming language** across various domains, from web development and data analysis to artificial intelligence and automation. As of 2025, the demand for Python skills continues to soar, with industry giants like Cisco, IBM, and Google leveraging its capabilities for their projects . Python's dominance in the technology sector is undeniable – it remains the **most requested programming language** in job postings across multiple industries, including finance, healthcare, technology, and entertainment.

The language's popularity stems from several key factors: its **user-friendly syntax** that resembles natural English, making it exceptionally accessible for beginners; its **versatile nature** that supports multiple programming paradigms; and its **extensive ecosystem** of libraries and frameworks that simplify complex programming tasks. Python's cross-platform compatibility ensures code runs seamlessly on Windows, macOS, and Linux environments, while its open-source nature has fostered a massive community of contributors who continuously expand its capabilities . These attributes make Python not just a programming language but a **comprehensive toolset** for solving diverse computational problems.

For professionals looking to future-proof their careers, Python offers **exceptional value**. According to industry data, Python developers in the United States earn an average of **$116,028 per year**, reflecting the high market demand for these skills . Beyond financial rewards, Python proficiency opens doors to cutting-edge fields like machine learning, natural language processing, and data analytics – domains that are shaping the future of technology across industries.

## 2 Course Overview & Learning Objectives

### 2.1 Course Philosophy
This Python programming course is designed with a **practice-oriented approach** that emphasizes hands-on learning and real-world application. Unlike traditional programming courses that focus heavily on theory, this program balances conceptual understanding with **practical implementation**, ensuring students develop the skills needed to solve actual business problems. The curriculum is structured to build proficiency gradually, starting with fundamental concepts and progressing to advanced applications, with each module incorporating **project-based learning** components.

### 2.2 Key Learning Objectives
Upon successful completion of this course, students will be able to:

- **Demonstrate proficiency** in core Python programming concepts including data structures, control flow, functions, and file handling
- **Develop functional applications** using Python for various domains including web development, data analysis, and automation
- **Implement object-oriented programming** principles to create modular, maintainable code
- **Utilize popular Python libraries** such as Pandas, NumPy, and BeautifulSoup for specialized tasks
- **Integrate with databases** and web APIs to create full-stack applications
- **Apply debugging and testing** techniques to ensure code quality and reliability
- **Build portfolio-worthy projects** that demonstrate marketable skills to potential employers

## 3 Instructor Qualifications & Experience

### 3.1 Professional Background
**Amr** brings an exceptional **twenty-year track record** of development and instruction experience to this Python course. His extensive background encompasses both corporate training and software development, providing a unique blend of pedagogical expertise and practical knowledge. With credentials including a **Bachelor of Computer Science and Management Technology** from Modern Academy and a **Computer Science Diploma** from Arab Academy for Science and Technology, Amr possesses the academic foundation to complement his extensive professional experience.

His career demonstrates **progressive responsibility** and expertise across multiple programming languages and frameworks. Beginning as a technical instructor at renowned institutions including NewHorizons, Knowlogy, and Informatica, he quickly established himself as a developer at Microtech and ITS, where he worked on enterprise-level systems including **ERP and banking applications**. This combination of education and hands-on development experience creates an ideal foundation for teaching programming concepts with both theoretical rigor and practical relevance.

### 3.2 Industry Client Portfolio
Amr's exceptional teaching credentials are further enhanced by his impressive roster of **corporate clients**, which includes some of the world's most recognized brands:

- **Technology Leaders**: Microsoft, IBM, Siemens, Vodafone, and Telecom Egypt
- **Financial Institutions**: National Bank of Egypt, NSGB, CIB, and Central Bank of Egypt
- **Global Consumer Brands**: Pepsi, Coca-Cola, Nestlé, Cadbury, and Americana
- **Industrial Conglomerates**: Chrysler, Valeo, 3M, ABB, and BP (British Petroleum)
- **Government Entities**: Libya Government IT Department, Sudan Army Officers, Egyptian Airports Company

This diverse client experience has provided Amr with **unparalleled insight** into how Python is applied across different industries and organizational contexts. His exposure to various business domains allows him to teach Python not as an abstract academic exercise but as a **practical tool** for solving real business problems.

### 3.3 Teaching Methodology
Amr employs a **learner-centered approach** that emphasizes interactive engagement and practical application. His teaching philosophy is based on the principle that programming is best learned through doing, rather than passive listening. Each concept is introduced through **clear explanations** followed immediately by hands-on exercises that reinforce learning. He adapts his pace and approach based on student comprehension, ensuring no one is left behind while maintaining challenging content for advanced learners.

*Table: Instructor's Recent Training Engagements (2023-2025)*

| **Year** | **Corporate Clients** | **Training Centers** | **Technologies Covered** |
|----------|-----------------------|----------------------|--------------------------|
| **2023** | International Finance Corporation, Raya Integration | Raya Academy, IT-Egypt | VBA, Office Automation, Web Technologies, Software Fundamentals with C#, SQL Server Database Design and Querying, Introduction to .NET Core Framework, Building ASP.NET Core Web API, Front-End Development Basics (HTML, CSS, JavaScript, TypeScript), Advanced Front-End Development with Angular, Integration and Deployment |
| **2024** | 3M, Pepsi | NewHorizons, Radio & Television Institute, Informatics (Lebanon), Total-Tech (KSA), Global Business Star (USA) | SQL Query (20761), SQL Development (20762), SQL Admin (20764,20765), Tabular, MQL5, ASP.NET Core MVC Web Applications (20486), Programming in C# (20483), Programming in HTML5 with JavaScript and CSS3 (20480), LINQ, EF (Entity Framework) |
| **2025** | Siemens, Vodafone | YAT, Future University | Full Stack Development, Data Analysis |

## 4 Detailed Course Curriculum

### 4.1 Module Breakdown
The Python course is structured into **eight comprehensive modules** that systematically build programming proficiency from foundation to advanced application:

1. **Python Fundamentals** (10 hours): Syntax, variables, data types, operators, and basic input/output operations. Students will write their first programs and understand how Python interprets and executes code.

2. **Control Structures & Functions** (15 hours): Conditional statements (if/elif/else), loops (for/while), function definition, parameters, return values, and scope. Emphasis on writing clean, reusable code.

3. **Data Structures** (20 hours): Lists, tuples, dictionaries, sets, and their appropriate applications. Includes comprehensive exercises on data manipulation and storage.

4. **Object-Oriented Programming** (20 hours): Classes, objects, inheritance, polymorphism, and encapsulation. Students will learn to structure code using OOP principles for better maintainability.

5. **File Handling & Modules** (10 hours): Reading/writing files, exception handling, importing modules, and creating custom modules. Practical applications for data persistence.

6. **Web Development with Python** (25 hours): Introduction to Flask/Django frameworks, REST APIs, and basic front-end integration. Students will build a functional web application.

7. **Data Analysis & Visualization** (25 hours): Using Pandas for data manipulation, NumPy for numerical computing, and Matplotlib/Seaborn for visualization. Real-world datasets will be used for analysis.

8. **Introduction to Automation & Scripting** (15 hours): Applying Python to automate repetitive tasks, web scraping with BeautifulSoup, and working with APIs.

### 4.2 Practical Projects
The curriculum includes **five portfolio projects** that allow students to apply their learning:

1. **Data Analysis Project**: Analyzing real business data to extract insights and create visualizations
2. **Web Application Project**: Building a fully functional web application with database integration
3. **Automation Script**: Creating a practical tool to automate a repetitive computer task
4. **API Integration Project**: Connecting to external services and processing returned data
5. **Final Capstone Project**: A comprehensive application that demonstrates mastery of course concepts

### 4.3 Python in Marketing Analytics
A special section of the course will focus on **Python applications in digital marketing**, covering how Python can be used for marketing automation, data analysis, and operations . Students will learn:

- **Working with APIs** to connect different software tools and automate marketing workflows
- **Web scraping** to gather data from web pages for content analysis and competitive intelligence
- **Text analysis** for sentiment analysis, content optimization, and customer feedback processing
- **Data analysis** for marketing analytics using Pandas and visualization libraries
- **Technical SEO** applications using Python libraries like advertools and EcommerceTools

This specialized content demonstrates Python's versatility beyond traditional programming roles, showing its value in business functions like marketing where data skills are increasingly crucial.

## 5 Training Methodology & Delivery

### 5.1 Interactive Learning Approach
This Python course employs a **multimodal teaching methodology** that accommodates diverse learning styles while ensuring practical skill development. Each session follows a structured pattern:

1. **Concept Introduction**: Clear explanation of programming concepts with real-world analogies
2. **Live Coding Demonstration**: Step-by-step coding examples that students can follow along
3. **Guided Practice**: Structured exercises with instructor support and immediate feedback
4. **Independent Challenge**: Problem-solving activities that require applying concepts creatively
5. **Code Review**: Collaborative analysis of solutions to identify best practices and improvements

This approach ensures that students not only understand theoretical concepts but develop the **problem-solving mindset** essential for effective programming. The emphasis is always on writing clean, efficient, and maintainable code following industry standards.

### 5.2 Hands-On Labs & Exercises
A distinctive feature of this course is the extensive **hands-on programming practice** integrated throughout the curriculum. Students will spend approximately **60% of course time** actively writing code rather than passively listening to lectures. Practical components include:

- **Coding exercises** for each new concept introduced
- **Mini-projects** that combine multiple concepts into functional applications
- **Debugging challenges** that develop problem-solving skills
- **Code optimization** activities focusing on efficiency and performance
- **Pair programming** sessions to foster collaboration and knowledge sharing

ِSend me if you have any questions,
Regars,
Amr

Nicolas

4.74

(27)

I am a dynamic and demanding teacher who gives private lessons in Physics-Chemistry as well as Mathematics.

I graduated from teaching seven years ago, after a masters in physical sciences with honors, and I teach in college and high school since.
I have also been preparing students for the Baccalaureate Science for many years, all of whom have been awarded very good honors.
I also prepare my students for different exams (Matu, Bac, preparation for EPFL, etc...)

I make sure to rework the basics so that the student can progress quickly. It is important to me that my students acquire a solid foundation of knowledge.
I also give effective work methods that will allow him to progress much more quickly and so he can regain self-confidence.

I can travel to the student's home or also conduct the lesson via Zoom/Google Meet.

Martin

4.74

(27)

Working part-time in the watch industry, I have been tutoring for several years in the context of refresher, occasional support or preparation of exams or competitions. Very experienced in relation to the difficulties encountered by students and pedagogue, I adapt to the needs of each to quickly regain the necessary confidence, the methodology of mathematical reasoning and allow a rapid improvement of results.
Experienced and pedagogue, I adapt to the needs of the student to help him consolidate his knowledge methodically, to regain confidence and improve as quickly as possible its results. I teach these courses in a radius of 30 km around Geneva.

Léo

4.74

(27)

• Teaching methodology and techniques: I favour a personalized approach, adapting the courses according to the profile and academic background of each student.
• Typical course structure: tutoring in economics, econometrics, statistics and probability, financial mathematics, trading, investment, or political economy. Courses can take place at home, via videoconference, or at a pre-selected location, ideally quiet, free, and conducive to learning.
• Specifics as a teacher: I offer support throughout the school year, with free corrections of exercises outside of class, regular availability, and the guarantee of being accessible until the end of the year, subject to the general conditions of Superprof.
• Target audience: all levels, regardless of diploma, class or specific characteristics.
-------
The path and the method are in there; take a little bit of each.

Holding a degree in mathematics from EPFL, I offer private lessons in Geneva or online.

I graduated from EPFL with a degree in mathematics, having completed all the Bachelor's level courses in this discipline. I have gained significant experience tutoring students from middle school to university level (mathematics and physics). I have also assisted with teaching at EPFL, particularly in specialized courses such as analytic geometry (advanced mathematics course), analysis (first and second year Bachelor's level), and linear algebra (first year Bachelor's level). My in-depth mastery of the theory in these disciplines provides me with the skills and teaching abilities necessary to effectively support high school and university students, helping them understand the theoretical concepts in their courses and apply them practically in their exercises.

Typical course: a quick review (adapted to needs) of the essential concepts of the course, followed by practical exercises and oral role-playing (going to the board, discussion on the physical meaning, etc.), as in a competitive oral exam.

All my lessons are prepared in advance based on the topics covered in class (the student specifies their needs from one session to the next). I also create a handout containing sample exercises illustrating different methods, fully corrected and explained by me.

My commitment to my students' success is absolute. I only prioritize motivated students who are ready to put in the necessary effort to progress.

My main focus is on in-depth understanding and the quality of work. Depending on the student's request, I can also suggest exercises to do between sessions (not mandatory, depending on available time and homework already assigned by their school).

Ali

4.74

(27)

I offer one-to-one Machine Learning and AI tuition for university students, postgraduates, working professionals, and serious self-learners. Lessons are available online or in person around Birmingham.
What I cover:

Python for data science and ML (NumPy, Pandas, Scikit-learn)
Deep learning with TensorFlow and Keras
Core ML concepts: regression, classification, clustering, neural networks, CNNs
Computer vision and image classification (my published research area)
University coursework support, dissertation help, project guidance
Help with Kaggle competitions and personal portfolio projects

How I teach:
I focus on understanding, not memorisation. We work through real datasets and real problems — not toy examples — so you can actually apply what you learn. I'll help you build a model from scratch, debug it when it doesn't work, and explain the maths behind why it does or doesn't perform well. For university students, I can also help with assignments, dissertations, and final-year projects.
Whether you're just starting out, stuck on a coursework project, or trying to break into ML professionally, I can meet you wherever you are and help you move forward.

Ammar

4.74

(27)

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.

Nuria

4.74

(27)

Do you want to learn Artificial Intelligence from scratch or do you need support with a subject, practice or project related to AI?

The classes are online, one-on-one, and fully tailored to your level and goals. We can work from the fundamentals to practical applications using Python, generative AI tools, language models, and APIs.

We can work on content such as:

fundamentals of Artificial Intelligence;
Python applied to AI and data processing;
data preparation, cleaning and analysis;
NumPy, pandas and data visualization;
Introduction to Machine Learning;
classification, regression and model evaluation;
Generative AI and Language Models (LLM);
use of ChatGPT, Gemini and other AI tools;
design and improvement of prompts;
consumption of AI model APIs;
task automation using AI;
AI integration in applications;
search and work with information and documents;
development of small projects and prototypes;
internships, projects and exam preparation.

The goal is not only to learn how to use AI tools, but to understand how they work, when to use them, and how to practically integrate them into your own projects.

We can start from scratch, work on the syllabus of your subject, or develop a specific application or project step by step.

In addition to the classes, you will have access to our educational platform with its own documentation, exercises, examples, practices and other resources to continue working between sessions.

Additional information for the student

You can bring your own syllabus, practical exercises, data, or project. We will adapt the classes to your prior knowledge and the objective you want to achieve.