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My formation in engineering school (Information Technology at the ÉTS in Montreal, Canada), techinian school (GEII at the IUT de Cachan, France) and my previous placements experiences (Croesus Finansoft and the National Institute of Sports) helped me specialize myself in Math, Physics and Computer Sciences. I'm able to teach and help the students in Math, Physics and the basic of Computer Sciences (depending on the student's level). The focus of the class is to develop the ability to learn, think and solve problems. As for the Computer Sciences class, you will learn the basics of current programming languages such as C/C++, Java, Python, Objective C (IOS programming). At the end of the class you could have some homeworks to do for the next session. These would help you to assimilate the subject previously learned.

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In this comprehensive tutoring course, students will gain mastery in Math, Computer Science, and **Programming** through personalized lessons tailored to their learning needs. Whether you're tackling high school math (algebra, calculus, geometry) or diving into the world of computer science (algorithms, data structures, logic), I provide clear, step-by-step guidance to help you succeed. Students will also build hands-on coding skills in Python, Java, and C++, working through real-world examples and projects that enhance their understanding. Designed for learners at any level, this course ensures you develop the confidence and expertise needed to excel in academics and beyond.

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As a tutor, my goal is to create a supportive and engaging learning environment where students feel confident to explore and grow. I tailor my teaching style to suit each student's unique needs. My focus is on building a solid foundation in algorithm and computational concepts and fostering critical thinking, helping students not only understand the material but also develop independent problem-solving skills. For parents, I value open communication and progress updates, ensuring they are informed and involved in their child’s learning journey. My background in mathematics and data science allows me to approach problems from both analytical and practical perspectives, giving students valuable insights into real-world applications of what they learn.

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C language is a very simple and basic language to learn, thus a very powerful one. With this course, I will introduce you to the concept underlying the C language and I will teach you the best practice when working with it. If you have any issue regarding this language, please get in touch and I will be happy to help

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Android Development complete course starting from basic app building to developing major projects. The course will cover the following topics - 1. Introduction to Android Development 2. Android studio installation and overview 3. Creating layouts for app using XML 4. Developing Currency converter and Calculator app. 5. Adding animation and media (images, video, sound). 6. Creating list view and Recycler view (advance list view). 7. Developing a Stopwatch app. 8. Async Task (doing background processing). 9. Understanding and applying Intents. 10. Understanding and using libraries(Google libraries and Shared Prefs). 11. Fragments 12. Creating a View Pager. 13. Handling exceptions (try/catch/finally). 14. File Handling in Android. 15. Broadcasts in Android 16. Notifications 17. Services OPTIONAL - 1. Firebase basic working. 2. Event bus (library to ease data passing) 3. Basic game development After the course, students will be capable of building advance apps from designing the basic layouts to fully functional app. The teaching method will consist 80% practical and 20% theory as I believe its better to show how it works rather talk about it.

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<Course Description> This course is designed for beginners who are interested in learning programming with Python. It covers the basic concepts of programming such as data types, variables, control structures, functions, and file I/O. Participants will learn how to write Python programs, debug code, and design algorithms using Python. The course also introduces the basics of object-oriented programming and the Python libraries used for data manipulation and visualization. <Prerequisites> No prior programming experience is required. However, familiarity with basic computer concepts such as files, folders, and operating systems is recommended. <Learning Objectives> By the end of the course, participants will be able to: * Understand the fundamentals of programming and how it applies to Python * Write Python code for simple applications and automate repetitive tasks * Use control structures such as loops and conditional statements * Create functions to encapsulate code and enable code reuse * Work with Python libraries such as NumPy, Pandas, and Matplotlib * Use object-oriented programming principles to design more complex programs * Debug code and use error-handling techniques <Course Outline> The course is divided into modules that build on each other to provide a comprehensive introduction to Python programming. Each module consists of lectures, demonstrations, hands-on exercises, and quizzes to reinforce learning. Here is an outline of the course: Module 1: Introduction to Python History and Overview of Python Setting up Python environment Writing and running basic Python programs Variables, data types, and operators Module 2: Control Structures Conditional statements and Boolean logic Loops and iteration User input and output Module 3: Functions Writing and calling functions Scope and namespaces Return values and parameters Lambda functions Module 4: File Input and Output Reading and writing files File modes and buffering Handling exceptions and errors Module 5: Object-Oriented Programming Classes and objects Inheritance and polymorphism Data encapsulation and abstraction Special methods and decorators Module 6: Python Libraries Introduction to NumPy, Pandas, and Matplotlib Data manipulation and analysis with Pandas Data visualization with Matplotlib Conclusion This beginner's programming class in Python provides a solid foundation for anyone interested in learning programming and using Python for data analysis, automation, or software development. With hands-on exercises, interactive quizzes, and a comprehensive final project, participants will learn how to write Python code that is efficient, maintainable, and elegant.

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MsC in Engineering with top marks and research assistant of Econometrics for Italian top University. Business Expert in Risk Management. Academic Research in Quantitative Finance and Algorithmic Trading. Common discipline covered: Econometrics (with applications in R, Stata, SPSS, Eviews, Gretl), Statistics, Financial Mathematics, Quantitative Support for Master Degree Thesis (from Regressions to all statistical applications), Risk Management, Mathematics, Computer Science I help with assignments, exams, presentations, advanced research, dissertations, big programming projects and general skill enhancement. Proficient in all major statistical packages: R, SPSS, Stata, Matlab, EViews, Gretl Technical Skills (application and often implementation from scratch): 1) Econometrics: Multivariate Regression, Discrete variable models (i.e. Logit), Time series models (i.e. AR/MA, ARCH/GARCH), Vector AutoRegressive model (VAR), Cointegration (Engle-Granger, VECM), Long-memory process (Fractional Integration), Regime switching models (Hamilton Filter), Kalman Filter, Unobserved Components ARIMA model, Beveridge-Nelson decomposition (Hansen's approach), Copula methods, Metropolis-Hastings algorithm, Black-Litterman model (Meucci's approach), Hierarchical Risk Parity 2) Quantitative Trading (Mid-High Frequency Trading): Stat Arb & Pairs Trading models, Order Imbalance & Order Replenishment effects on intraday returns, Optimal Setup of Entry-Exit Trading Triggers for Quant Trading Strategies, Stat Arb Bertram Model, Data sampling rules for non equally-spaced data (time vs. volume clock for high freq data), Bid-Ask Bounce Bias & Sahalia Method for Microstructure Noise Estimation & Test, Hayashi-Yoshida Lead-Lag Index, D'Aspremont Method for Mean Rev Portfolios, Market Fragmentation in Financial Markets, High-Low prices & Pivot Points trading rule, Trend Following Strategy, Avellaneda-Stoikov Model for Optimal Trading Execution 3) Risk Management: P&L production & analysis for energy trading, VaR & Profit at Risk for energy trading, Merton approach for Credit VaR with/without credit rating migrations, EVT & Copula-based VaR, Stress Test models, Structured Credit Models for Regulatory Risk-Transfer, Additional Value Adjustments for Balance Sheet, Risk Aggregation, Model Risk, Interpolation Methods for multi-year PD Term Structure, Methods for Semidefinite-Positive Corr Matrix Adjustment 4) Financial Mathematics: Longstaff-Schwartz, HJM model (Glasserman's scheme), Greeks with Finite Difference Method, CPPI Products & Cushion Multiplier Setup 5) Machine Learning: Support Vector Machine, Decision Tree, Principal Component Analysis & Regression, XGBoost, Random Forest

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Hi, I hope you will be fine. Welcome to my profile. This is Faisal. I am a Lecturer in Data Science at University. Data Science is the advanced field of Computer Science. I have more than 4 years of teaching experience including International level Students from Multiple countries of different levels of education, like, up to the University level. I love education because education is a powerful weapon to change the world. I am hardworking, and I am interested to use my Technical background and Expertise for my students. I teach the students with step-by-step instructions to make their concepts clear. That’s why I always focus on the Quality of Education to make my students and their parents happy. I take quizzes /tests daily and weekly basis. I provide the helping materials. I'm a friendly, happy, and polite person. I really like teaching because I think it’s my passion. I really enjoyed teaching children because they always enjoy my lessons. Lооking fоrwаrd tо Help mоre аnd mоre students tо get better & Quаlity Educаtiоn. Feel free to contact me, Takecare :)