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Computer programming lessons in Utrecht

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8 computer programming teachers in Utrecht

Trusted teacher: 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
Statistics · Economics for adults · Computer programming
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Trusted teacher: Hello, I am a doctoral student in electrical engineering and associate professor in engineering sciences, experienced in the field of electrical engineering, I offer support courses in the subjects of engineering sciences (Electronics, automatics, electrical engineering, automation, programming). Digital electronics Analog electronic electromagnetism (propagation of high frequency waves) Automatic (continuous, sampled) electrical engineering (transformers, electrical machines, switching power supply) C / c ++ programming, Assembler, ARM, STM32 renewable energy (wind, PV) engineering Sciences RDM Python,VHDL PIC Microprocessor and Microcontroller Signal processing and data acquisition Engineering Sciences These courses allow the student to get up to speed and regain confidence in all scientific subjects, just as they prepare him effectively for the Baccalaureate, the Preparatory Classes or various examinations of the engineering classes. COURSE OBJECTIVES AND PEDAGOGICAL APPROACH Resumption and deepening of fundamental concepts through exercises with course reminders. Put the student in a situation of questioning and research. Respond to individual issues and questions Exercise training in order to achieve real mastery of the content. Learn to build theoretical reasoning from observable facts or hypotheses. Specific preparation for higher education requirements (in-depth content, increase in work capacity, enrichment of scientific background) This educational approach is effective since it has often led me to interesting results with my students. Associate professor provides support courses in electrical engineering
Computer programming · Electronic circuits · Electrical engineering
Computer programming · Investing · Financial markets
Trusted teacher: Master pseudo-code algorithms in this hands-on course with dozens of different algorithms In this course, you will learn the basics of computer programming through the fundamental subject taught in all higher schools of computer science: algorithms. This is the initial stage of your learning to become a computer scientist (programming) First we will see a broad introduction to computer programming, and we will explain what algorithms are. Then, you will learn the language of computer scientists by studying "pseudo-code", and you will learn all the concepts of computer science through a multitude of practical exercises. The topics covered are very broad and comprehensive: Introduction - Algorithm Syntax - data type and Variables - The operators - The instructions - Conditions - The repetitive structure (loops) - The tables - Research techniques - Sorting algorithms - dichotomous search - Functions - The procedures - Recursion -complexity - Introduction to the C language - ... Your first programs... Finally, you will start programming by creating several algorithms in a specific programming language (here, C language). These algorithms are applicable in all programming languages. The goal... With more than 8 hours of e-courses, quizzes, and an assessment, you will have what you need to continue your learning of computer programming and advance towards your future profession. Who is this course for? Beginner in programming Retraining Computer science students or future students Thanks and see you soon ! IMAD
Computer programming · Algorithms · Computer science
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Only reviews of students are published and they are guaranteed by Apprentus. Rated 4.9 out of 5 based on 225 reviews.

Private coding / programming lessons with python (Paris)
Matías
Highly recommended teacher!!! Matias teaching methods are great. Very clear and concise. Doesn’t waste your time explaining meaningless background information and always lectures with the intent to help you understand the material. He’s helped me understand content for my master course on Python and is one of the best lecturers that I’ve had. Your passion and dedication is beyond words! Thank you for getting me through this hard quick semester, I honestly would have never passed if it was not for your help! Thank you so much once again!
Review by JURIS
Scientific subjects (Math, Physics, Chemistry) for students of the French mission/for middle and high school students (Casablanca)
Amin
So far, I've been getting help with my IGCSE 's in Math and Computer Science with Amin. In most of the lessons I've been with him, he's been really helpful and responsible. He has also been very patient. He helps me become more confident in my answers and makes the lessons pretty fun! After my lessons with him, I do understand my topics more and am able to go to my classes in school without feeling lost. If you're ever struggling with Physics or Programming, I'm sure he can help you too :)
Review by MANIJ
Mastering Web Development: From Fundamentals to Advanced Techniques (Tunis)
Oussama
I have no prior experience in this area and I took lessons with Ousamma. He has enough patience and a knack in guiding you step by step through the lessons and exercises in a very simple way to understand them well. He is an invested teacher that is kind and polite. He will help you to develop your abilities and to feel confident in order to achieve your goals. I warmly recommend him and extend my gratitude his great support throughout my learning journey.
Review by BEN