3d max + Vray or Corona, special course of interior visualization.
This course will tell you how to create photo-realistic renders fast and easy, based on my own 7 years experience in CG and interior design.
Basic part (for beginners):

- Basic interface features and main modifiers which can be used for interior visualization
- Scene preparing and composition
- Basic scene assembling and Modeling
- Light and camera setting
- Render settings

Advanced part (advanced users) :

- 4 different room types, creating from scratch (living room, bedroom, kitchen, bathroom)
- Advanced camera, light and render adjustment
- Composing and retouching multilayered render (Photoshop)
- Professional hints and tricks in interior visualization and design

Duration:
Individual plan, one-on-one lessons via Skype based on flexible schedule, 1 lesson - 1.5 hours

Basic part (for beginners): 4.5 - 6 hours
Advanced part (advanced users) :9 - 12 hours

Organisations are welcomed.

Hi, I am a very patient and motivated tutor. I will do my best to deliver excellent and quality learning that match my expertise.

(A) Teaches B.Sc. Biotechnology students in BIMS, Burdwan, WB
(B) Preferred: Graduate & Post Graduate in Zoology, Entomology, Molecular Biology, Biochemistry
(C) Brief Resume
ACADEMIC APPOINTMENTS AND EXPERIENCE:
1. Defence Research Laboratory (DRDO)
Post Bag No. 2,
Tezpur–*, Assam, INDIA
Junior Research Fellow (JRF)
(PhD scholar), 2 years
Senior Research Fellow (SRF
(PhD scholar), 3 years
2. National Centre for Disease Control (Min. of Health & FW) Deputy Assistant Director (Entomology) Present
PUBLICATIONS:
International: 8rnConference: 7
EDITORIAL RESPONSIBILITYrnAssociate Editor in Journal of Entomology & Nematology (ISSN:2006-9855) from August 2009
PROFESSIONAL MEMBERSHIPrnNational
I. National Academy of Vector Borne Diseases, India (Life member
II. Zoological Society of Assam, India (Life member
III. Indian Science Congress Association, India (Member
IV. Entomological Society of India (Member
International
I. International Society of Zoological Science, China (Member
II. International Society for Infectious Diseases (Corresponding Membership
III. The International Society of Integrative Biology (Online Member
IV. South-South Initiative for Tropical Disease Research (Online Member

SUPERVISION OF STUDENTS FOR TRAINING/COURSErnI supervised six B.Tech (Biotechnology) students for their training/course in 2008 & 2009.
HIGHLIGHTS OF EXPERIENCE / RESEARCH SKILLS
Basic Zoology/Entomology
•Identification of medically important insects, especially mosquitoesrn•Establishment & rearing of insecticide susceptible and resistant insectaries (mosquitoes & house fly)
•Insecticide Resistance Management & Integrated Vector Control Strategiesrn•Knowledge of insecticide testing techniquesrn•Working knowledge of pesticide application techniques & equipmentrn•Determination of Plasmodium sporozoite rates in Anopheles mosquitoes by dissection, CS-ELISA & molecular methodsrn•Mosquito blood meal analysis through ELISA & PCR methodsrn•Entomological measures of risk of malariarnBio–Toxicity / Susceptibility Assay:
•Insecticide susceptibility assay, status monitoring, & management
•Bioassay of insect both larvae & adult against chemical insecticides
•Evaluation of herbal and bacterial larvicidesrnMolecular Biological Techniques
•Genomic DNA preparation from insects, fungus and malaria parasite by different methodsrn•Polymerase Chain Reaction (PCR): standard PCR, allele-specific multiplex PCR, nested PCR etc.; agarose gel electrophoresis, automated DNA sequencingrn•Real-Time PCR; TaqMan, SimpleProbe, HybProbe probe chemistry; Melting Curve Analysis, FRET/MCA; quantitative real time PCRrn•Restriction Enzyme digestion of DNArn•RNA isolation, Reverse Transcriptase PCR & cDNA synthesisrn•Cloning & gene expression
•Different types of sequence analysis, Primer designing (standard, allele-specific, degenerate, species-specific primers), Probe designing for SNP genotyping (TaqMan, SimpleProbe, HybProbe
Biochemical Techniques
•Spectrophotometric analysis of DNA, enzymes, proteins and other bio-moleculesrn•Estimation & quantification detoxifying enzymes & protein profiling: glutathione S-transferase, Cytochrome P450/Monooxigenase, Carboxylesterase, Acetylcholinesterase.
•Circum Sporozoite ELISA methodrn•Mosquito blood meal ELISA methodrnStatistics & Bioinformatics
•Different biostatistical analysis involving wide range of data from epidemiological, entomological, molecular, and other biological studiesrn•Expert in handling Statistical software packages like STATPACK, SPSS, and STATISTICArn•In Silico and mathematical Modeling of proteins: comparative protein Modeling, structure validation, functional residue prediction and docking (protein-protein, protein-ligand)
•Sequence analysis & annotation including similarity search, alignment, gene finding (ORF), database mining etc
•Phylogenetic analysis, Tree construction algorithms (NJ, parsimony, maximum likelihood methods
•Analysis of population genetics parameters
•Analysis of molecular evolutionary data: DNA polymorphisms, divergence, gene flow, genetic difference, linkage disequilibrium, recombination, different tests of neutrality (Tajima’s D, Fu & Li’s D, F test etc.), coalescent simulation etc
•Expert in handling software packages for molecular biological & evolutionary studies (e.g., BioEdit, Arlaquin, DnaSP, MEGA, DAMBE, and Mesquite etc.)

I am new to tutoring but am patient and enthusiastic about programming.

I have done MBE followed by Bachelors in Economics.
I have more than 3 years of experience in data analysis and reporting.
I have advanced exposure of MS-OFFICE like EXCEL & ACCEESS and some other statistical tools like SAS, MINITAB to do statistical analysis and Modeling.
I am very cool tutor :)

Hello everyone

I am Morgan and I would like to help you with your :
Maths : from primary school to VCE, year 11 year 12 (further maths, specialist maths, maths methods), to university level 1 level 2 maths, including calculus

Physics : from VCE to level 1 and 2 university physics

Mechanical Engineering : University level 1 and level 2

French : all levels, including oral conversations, writing essays, exams supports

I'm Morgan and 24, and I'm in my 5th year of a 5-year master's of engineering. Now I am doing my internship about material research in Melbourne university until July, then I'll do a PhD about Mechanical Engineering. I have intensive teaching experience in Maths/Physics/French/Mechanical Engineering. Indeed, I came in Melbourne one year ago, and I taught several students. I used to teach in France as well. I am very patient, reliable and motivated

After two very selective years and competitive written and oral exams, I studied in "grandes ecoles" in France, which are special prestigious elite universities, providing me a high level in the above subjects mentioned. Therefore, I can teach level 1, level 2, university level including mathematics, physics and mechanical engineering

I had high score in the TOEIC (Test Of English for International Communication) with a score of 945 over 990. I have also published an article entitled "Modeling of Cracking in Laminated Composites"

During a class, we can focus on theory and peculiar concepts the student didn't understand. I can help him to do his homework as well. At the end of every class, I can give him 3-4 more exercises. I will correct them at home and give the answers the following week

I'm available on weekends and after 5PM during the week. I'm living in Brunswick and going to Melbourne Uni everyday

If you need some more information, please let me know. (for instance resume)

I'm looking forward to working with you

Morgan

I have demonstrated my educational ability in various institutions around the world stretching from London to the Middle East since the early 1990s. I have in depth knowledge of my subject areas; hence i find creative ways to help my student relate to the subject material. I can teach anybody no matter how academically challenged they are, provided they want to learn.

TEACHING EXPERIENCE 20 YEARS.
I AM A VERY PATIENT TUTOR.

Relevant Units covered in Undergraduate Studies.• Applied Mathematics-1( Complex Variables, Vector Algebra, Calculus Taylors theorem, expansion of functions
in power series, partial derivatives of first and higher orders, total differentiation concept of commutative partial derivatives, Eulers theorems of homogeneous functions, deduction from Euler’s theorems ,errors, approximations, maxima and minima functions of two variables.)
• Applied Mathematics-2( Exact differential Equations, Linear equations & reducible to linear (Bernoulli equations), Linear Diff. Eqn. of nth order with constant coefficients, complimentary function & particular integral when the function of the
integral on the R.H.S. are exponential, Sin(ax + b), Cos(ax + b).Cauchys Linear equation( Homogenous eqn.). The Legendre Linear equation, Variation of parameters & method of undetermined coefficients. Elementary application of above diff. Eqn. in solving engineering problems from Electrical Engg., Chemical Engg., Mechanical Engg., and Civil Engg. Integral Calculus: Rectification of plane curves, Double and Triple integrals, Their geometrical interpretation & evaluation. Evaluation of double integrals by change of order and change to polar. Application of double and triple integrals to areas, volumes & mass. Beta & Gamma Functions.)

• Applied Mathematics 3(Fourier Series and Integrals: Orthogonal and orthonormal functions, expression of a function in a series of orthogonal functions,s ine and cosine functions and their orthogonality properties. Fourier series, Drichlet conditions, periodic functions, even and odd functions, half range sine and cosine series, Parseval's relation. Complex form of Fourier series, introduction to Fourier integral, relation with Laplace transform. Laplace Transforms: Function of bounded variable ( statement only ), Laplace transforms of 1, at, exp( at ), sin( at ), cos( at ),sinh(at), cosh(at), erf(t), shifting properties, expressions with proofs for L { t f(t) }, L { f(t)/t }, Laplace of an integral and derivative)

• Applied Mathematics 4(Complex Variables: Regions and paths in the Z plane. Path/Line integral of a function. Inequality conditions for a path integral to be independent of the path joining two points. Contour Integral, Cauchy's theorem for analytical functions with continuous derivatives. Matrices: Brief revision of vectors over real field, inner product, normal, linear independence, orthogonality. Characteristic values and vectors, and their properties for Hermitian and real Symmetric matrices. Vector Calculus: Scalar and Vector point functions, directional derivative, level surfaces, gradient, surface and volume integrals, definition of curl, divergence. Use of operator. Conservative, irrotational, solenoidal fields. Green's theorem for plane regions and properties of line integral in a plane.)

• Applied Mathematics 5(Probability and topics in Statistics: Statistical experiments with random outcomes, Sample space, probability defined on the basis of sample space and on the basis of events and their combinations. Theorem on probabilities, conditional probability. Bayes theorem. Random variable, probability distribution for discrete and continuous random variables. Density function and distribution functions. Expected values, variance , moments, moment generating functions, Bernoulli's trials, Binomial , Poisson, normal distributions for detailed study with proof, Other common distributions, T , F, Beta, Gamma, X with indication of the applications, Central limit theorem, Bivariate probability and frequency distributions, Correlations, regression, lines of regression. Introduction to random samples, use of random numbers, stochastic processes, Time series , queuing theory. Optimization Techniques- Problem formulation, Simplex Method, Revised Simplex Method, Duality & Sensitivity. Unconstrained optimization of several variables• Numerical methods for unconstrained optimisation : Random search & Univariate method, Fletcher Reverse method, Newtons method.)
• Discrete Mathematics ( Logic : Propositions and logical operations, Truth tables, Equivalence and implication, Laws of logic, Mathematical induction and quantifiers. Set theory : Method of proof for set, Venn diagram, set membership tables, definitions, Laws of set theory, Partition of sets. Permutations, combinations and discrete probability. Introduction to permutations and combinations, Generation of permutation and combination, Discrete probability, Conditional probability. Relations and diagraphs., Paths and the relations and diagraphs, Properties of relations, Equivalence relations, Computer representation of relations and diagraphs, Manipulation of relations, Transitive closure, Warshall’s algorithm.Function and pigeon hole principle Definition, Types of functions: injective, surjective, bijective, Composition, identity and inverse, Pigeon hole principle.Graphs , Posets, Hasse Diagram, Lattices, Finite Boolean Algebra, Groups & their Applications Introduction to Rings & Fields.)

Units covered in Postgraduate Studies.
• Advance Financial Mathematics (Access Grid Room -University of Wollongong): Brownian motion, Black-Scholes equation for pricing Digital options and Power options, Reflection principle and barrier options, Pricing options using Monte Carlo Simulations, Monte Carlo estimation methods for hedge ratio, Finite-difference methods for Vanilla options and Asian Options, C++ Programming.
• Financial Econometrics 2 (Monash University):Modeling asset return volatility, volatility Modeling for measuring risk and pricing derivatives, continuous time stochastic Processes for pricing financial Derivatives, High Frequency data Analysis, Generalized Method of Moments in Financial Models.
• COMPUTATION IN Stochastics (Monash University): Stochastic differential equations, Taylor expansion of stochastic differential equations, Evaluation of option values. European option. American option, Optimization methods using C++.
• STOCHASTIC CALCULUS AND MATHEMATICAL FINANCE (Dr. Fima Klebaner- Monash University): Ito integrals and Ito’s formula. Stochastic Differential Equations and Diffusions, Calculation of expectations and PDE’s, Feynman-Kac formula. Martingales and Semi martingales. Change of Probability Measure and Girsanov Theorem. Fundamental Theorems of Asset Pricing. Change of Numeraire. Application to options.
• Stochastic Processes II - Random Walks & Markov Chains (Monash University): Simple Random Walks Discrete-time martingales. Markov chains, both continuous and discrete time.
• Applied Statistics: Sample Survey, Clustering, Classification, Principal Component Analysis and Time Series Analysis. (79/100).
• Game Theory and Applications (RMIT University): Strategic Form of Games, Incomplete Information, Cooperative Games.
• Nonparametric Curve Estimation (AMSI - Dr. Aurore Delaigle-University of Melbourne): Kernal Density Estimation, kernel Regression, Spline Regression, Wavelet Analysis and Bootstrapping.
• Financial Time Series (Access Grid Room- University of South Australia): Spectral decomposition, Box-Jenkins models, Forecasting techniques, Smoothing of time series, GARCH and other volatility models, Stochastic Differential Equations.
• Statistical Inference: Statistical Inference at the level of Lee Bain and Max Engelhardt (2000).

As a Bio informatician & Electronics and Communication Engineer I have strong Combination of Statistics, Mathematics & Computer science. I am predominantly interested in joining a team which creates and drives new methodologies and technologies of future
My subsequent area of interest is Financial Engineering, Quantitative Finance (Discrete& stochastic Modeling of financial market) and data mining. I have sound Knowledge and experience of Hypothesis Testing, Regression Analysis and Random signal analysis. Time Seriese Analysis, Stochastic Process and Markovian Process Categorical Data Analysis.Class Prediction by K Nearest neighbor method, Support vector machine and neural network.Classification like Linear Disciminant Analysis, Quadratic Discriminant Analysis.Factor Analysis like Principal Component Analysis, Independent Componenet Analysis.Linear Algebra, Matrix analysis, Statistical Signal processing, Digital Signal Processing etc.

I am a very experienced University of London Graduate offering friendly and enthusiastic one-to-one tuition.

Sessions are tailored to suit the individuals needs and examination board requirements. All major exam boards catered for.