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from36.45USD/ h

Java Programming - Professional Specialized Training

From basics to real world professional problem solving skills:

Java introduction
Notions of Object Oriented languages
A beginner developer - step by step
Problem solving approaches in practice
Algorithms and data structures
Professional programming practices

Extra information

Laptop is not mandatory but is recommended

Location

At student's location: Around Brussels, Belgium
Online via webcam
At teacher's location: Grand-Place, 1000 Brussels, Belgium

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General info

Skills:
Age:
Preschool children (4-6 years old)
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:
30 minutes
45 minutes
60 minutes
90 minutes
120 minutes
The class is taught in:English

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Availability of a typical week

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from $36.45At teacher's location
from $36.45Online via webcam
from $42.70At student's home

Good-fit Instructor Guarantee


If you are not satisfied after your first lesson, Apprentus will find you another instructor or will refund your first lesson.

Online reputation

  • Instructor since May 2018

Availability of a typical week

(GMT -05:00) New York
MonTueWedThuFriSatSun
0              
1              
2              
3            Saturday at 3:00  
4            Saturday at 4:00  
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13  Monday at 13:00  Tuesday at 13:00  Wednesday at 13:00  Thursday at 13:00  Friday at 13:00    
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from $36.45At teacher's location
from $36.45Online via webcam
from $42.70At student's home

Good-fit Instructor Guarantee


If you are not satisfied after your first lesson, Apprentus will find you another instructor or will refund your first lesson.

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Youssef
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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

Steave
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Luca
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Sanyam
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Moad
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🔵 Core principle: The main criterion is to answer your questions in an interactive atmosphere and not to offer you an academic course! I offer you the first session of the course and adapt my formula according to your needs. 🔵 Profile: specialist in Mathematics and Computer Science (Engineer with double competence), experienced Data Scientist (with 4 years of experience), Research Assistant at the University of Luxembourg and future PhD student in Artificial Intelligence at Polytech Mons, I started tutoring, mainly in Mathematics, and a little in Computer Science when I was doing the preparatory classes MPSI-\ MP in 2013. Since then, I have had students of all levels - junior high school, Bachelor, Master - which has allowed me to improve my working method over time. I like the idea of being able to help students in difficulty, and it is a personal satisfaction to see a student's progress because it makes me useful. 🔵 My methodology will be as follows: I will explain abstract concepts (in the first few sessions), give you some suitable exercises, and leave you with exercises to do covering the challenges you encounter which we will solve together in the following sessions. I will also send you teaching material to accelerate your learning (summaries, videos, personal notes, websites, recommendations of relevant free courses, etc.).

Sunny
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Abdelilah
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Expert engineer in software development, I have 10 years of experience in the IT field, I want to share my theoretical knowledge and practice. For beginners, you will finally know the secrets of the world of software and you will have answers to your questions;)

Prajakta
Ms-office,C++,core java,android,vb.net,python,html,asp.net
I am Masters in Information Technology,I have 15 years o f experience in teaching field. If you would like to learn C.C++,Java,MS-office,android,python,vb.net,python,asp.net,html from basic level to intermediate level then i will help you.all the best

Zakaria
Database course (management, analysis) / SQL Programming.
Graduated in Management Informatics, having two years of experience as an IT trainer. I offer support courses and technical support in programming and database management. Programming Languages: SQL, PL / SQL, SAS Base.

Jay
Computer skills( Programming, Excel, Word, Powerpoint ,....)
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Mohamed
data processing
computer engineer offers help to master the known programming languages (.net, php, asp.net, html, ....). and also to help you master sgbd like sqlserver and mysql ... This course is for students who wish to prepare to become a Bachelor of Computer Science and for students who have computer skills in their degree programs.

Mattia
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

Zen
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Dia
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Fataou
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