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Since July 2022
Instructor since July 2022
JavaScript Classes - for Beginners and Intermediates
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From 23.63 C$ /h
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Javascript (JS ) is the language of the Web.

It is what adds Interactivity to any website you see.

You have probably also heard of JQuery, React, Angular, or Vue. Those are all frameworks for Javascript.

It is the main component used to build any website, and if you want to be a professional web developer, you are gonna need to learn it.

In this course, We are going to talk in the first session about you, your goals, and what you have achieved if you already started learning it. after that, I am going to prepare a plan that suits your goals.

about me:
I have been working in frontend Development for 5 years now, developing websites using JavaScript frameworks ( React, Vue, JQuery ).

if you have any questions or are unsure about whether it is the perfect way to start please feel free to get in touch with me.
Extra information
Bring your own Laptop.
Location
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At student's location :
  • Around Hørsholm, Denmark
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Online from Denmark
About Me
Hey there!

I'm Ahmed, a Senior Frontend Developer with over 8 years of experience creating websites using JavaScript frameworks (React.Js, Vue.Js, and jQuery).

Let's dive into the world of frontend development together!
Education
Degree: Bachelor of Engineering
Institution: Zagazig University, Zagazig, Egypt

- After completing my engineering degree, I transitioned into frontend development in 2018. Since then, I have been working in the field of frontend development, gaining valuable experience and expertise in this domain.
Experience / Qualifications
- Over 8 years of experience creating websites using modern SPA frameworks such as ReactJS, and VueJS.

- Knowledge of front-end design patterns and architecture, collaborating with designers to implement visually appealing and intuitive user interfaces based on mockups and wireframes.

- Proficient in using version control systems (e.g., Git) and working in collaborative development workflows (e.g., Agile, Scrum).

- Understanding of cross-browser compatibility issues and web performance optimization techniques.

- Experience with testing and debugging front-end code, identifying and resolving performance and functional issues.

- Up-to-date with the latest trends and advancements in front-end development, frameworks, and best practices.
Age
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Advanced
Duration
30 minutes
45 minutes
60 minutes
90 minutes
120 minutes
The class is taught in
English
Arabic
Reviews
Availability of a typical week
(GMT -05:00)
New York
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Online via webcam
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At student's home
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
Hi there,

I'm Ahmed, a Frontend Developer with 8 years of experience. I specialize in helping others learn Frontend Development from the ground up.

What I can teach you:

HTML/HTML5
CSS/CSS3 (including Bootstrap, Tailwind)
JavaScript and jQuery
SCSS/SASS
React, TypeScript, Mobx, Next.js
Vue, Vuex, Nuxt.js
Git/GitHub
Testing JavaScript applications (Cypress, Jest, React Testing Library)
WordPress Development (themes/plugins)

If you have any questions, feel free to reach out!
Read more
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Mattia
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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Mattia
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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