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Discover the Best Private Computer Programming Classes in The Netherlands

For over a decade, our private Computer Programming tutors have been helping learners improve and fulfil their ambitions. With one-on-one lessons at home or in The Netherlands, you’ll benefit from high-quality, personalised teaching that’s tailored to your goals, availability, and learning style.

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226 computer programming teachers in The Netherlands

Maiko

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$23

60-min

/h

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Introduction to Python Programming (algorithms, structures, abstractions)

Introduction to Python Programming (algorithms, structures, abstractions)

<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.

Mattia

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$82

60-min

/h

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Econometrics & Statistics (R, SPSS, Eviews, Gretl, Stata) for master thesis and assignments

Econometrics & Statistics (R, SPSS, Eviews, Gretl, Stata) for master thesis and assignments

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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Our students from The Netherlands evaluate their Computer Programming teacher.

To ensure the quality of our Computer Programming teachers, we ask our students from The Netherlands to review them.

Only reviews of students are published and they are guaranteed by Apprentus. Rated 4.5 out of 5 based on 14 reviews.

“ Sachin is incredibly knowledgeable, very punctual, polite. He always well prepared for the lesson. He teaches maths with right examples and makes sure that someone can get depth understanding. He makes me comfortable and always makes complex topics easy to understand. I found his teaching method very accessible and effective. ”

“ Mr. Akrem is a great teacher with patience and experience. He makes sure I as a beginner understood the basis of algorithms and how things work before actually coding which is a great thing. ”

“ He is a very professional and nice person. HIs technique is very effective to learn. As I learnt with him computer programming C ++ and it was very useful for me. Thanks Abhijit. ”

To ensure the quality of our Computer Programming teachers, we ask our students from The Netherlands to review them.

Only reviews of students are published and they are guaranteed by Apprentus. Rated 4.5 out of 5 based on 14 reviews.

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