Scientific programming using Excel VBA for beginners

Microsoft excel complete course beginner, intermediate & advanced - cou...

MS Excel Macros/ VBA Project report

Prafull Dhamankar

This document discusses the effectiveness of using macros and Visual Basic for Applications (VBA) for data analysis in Microsoft Excel. It provides an overview of how VBA can be used to automate repetitive tasks, create custom tools and reports. While VBA is useful for empowering analysts, the code it produces may not meet standards for professional programmers. Overall, VBA has been widely adopted due to its ability to meet analysis needs within Excel.

Big Data Processing with Azure Data Lake Analytics - Edukite

Microsoft excel 2016 advanced training - Adams Academy

Adams Academy

Microsoft Excel is used in businesses throughout, starting from engineering to diverse fields such as medicine. It is one of the top three best known Microsoft Office tools and probably the best spreadsheet program out there. However there is a steep learning curve to its advanced features, which you can now master from this Microsoft Excel 2016 Advanced Training course. See more: https://bit.ly/2jGOzNY

Ultimate Microsoft Excel Bootcamp - Course Gate

This document describes an online Ultimate Microsoft Excel Bootcamp course. The course aims to teach students all of Excel's functions from basic to advanced over 5 modules. It is suitable for anyone seeking to learn professional Excel skills regardless of experience. Upon completion, students will have an in-depth knowledge of Excel to help advance their careers working with spreadsheets. The course has received positive reviews from students who improved their Excel skills.

When you create real-world applications, the ability to store information in your program code is critically important. The aim of this course is make you learn how programming languages make use of various data structures to hold this information. You will learn how C# provides a plethora of data structures from simple arrays to more complex structures that permit the use of “typing”. See More: https://bit.ly/2Zbv0kB

Basic Principles of Behavior of Algorithms - Edukite

This course is a study of Behavior of Algorithms and covers an area of current interest in theoretical computer science. The topics vary from term to term. During this term, we discuss rigorous approaches to explaining the typical performance of algorithms with a focus on the following approaches smoothed analysis. In addition to that, condition numbers/parametric analysis, and subclassing inputs will be discussed. See More: https://bit.ly/2YCSkdn

Diploma In MATLAB for Scientific Computing – Edu Kite

This is a course which is more suitable for students who are interested in conducting research in scientific computing. This course includes teaching on linear algebra, numerical optimization, ODEs and PDEs. You will be introduced to advanced MATLAB features, syntax and toolboxes that were not included in the introductory courses. Advanced 2D/3D plotting, graphics handling, publishing quality graphics and animations, code optimization, object oriented programming and compile MATLAB in this course. See more: https://bit.ly/2vrEDxt

Boost Your Data Career with Predictive Analytics! Learn How ?

Edureka!

IJSRED-V2I5P42

IJSRED

This document summarizes a research paper on face detection using Haar-like features and an AdaBoost classifier. The paper proposes using new Haar-like features in addition to existing features to build a stronger classifier that can better detect faces. The methodology section describes training an AdaBoost classifier on the features to select important features and build a classifier. The face detection process then uses this classifier to scan images for faces. Experimental results showed the new feature classifier had a higher detection rate and lower error than a classifier using just original Haar-like features.

IRJET- Finding the Original Writer of an Anonymous Text using Naïve Bayes Cla...

This document discusses using a Naive Bayes classifier to identify the original writer of an anonymous text. It begins with an introduction to the problem and an overview of Naive Bayes classification. It then describes how a text can be represented as a bag-of-words with word frequencies and explains how Naive Bayes can be used to calculate the posterior probability and predict the class. The document compares the performance of Naive Bayes to other algorithms using an email dataset, finding that Naive Bayes has the highest performance factor due to its fast training and prediction times relative to its accuracy. It concludes that Naive Bayes can accurately predict the original writer of anonymous texts.

SAP BI Generic Extraction Using a Function Module.pdf

KoushikGuna

EnTagRec: An Enhanced Tag Recommendation System for Software Information Sites

Alexander Serebrenik

Software engineers share experiences with modern technologies by means of software information sites, such as Stack Overflow. These sites allow developers to label posted content, referred to as software objects, with short descriptions, known as tags. However, tags assigned to objects tend to be noisy and some objects are not well tagged. To improve the quality of tags in software information sites, we propose EnTagRec, an automatic tag recommender based on historical tag assignments to software objects and we evaluate its performance on four software information sites, StackOverflow, AskUbuntu, AskDifferent and FreeCode. We observe that that EnTagRec achieves Recall@5 scores of 0.805, 0.815, 0.88 and 0.64, and Recall@10 scores of 0.868, 0.876, 0.944 and 0.753, on StackOverflow, AskUbuntu, AskDifferent and FreeCode, respectively. In terms of Recall@5 and Recall@10, averaging across the 4 datasets, EnTagRec improves TagCombine, which is the state of the art approach, by 27.3\% and 12.9\% respectively.

Agent based modeling level 2 - edukite

This document describes an online course titled "Agent-based Modeling Level 2" that teaches how to build agent-based models from the ground up to understand complex systems in various domains. The course consists of 142 video lectures totaling over 21 hours. Students must complete 5 written assignments to pass the course, and have the option to pay a fee to receive an official certificate upon completion. The course content was created by the Santa Fe Institute.

Microsoft Office 2016 Excel Beginners - Course Gate

Arduino Based Scientific Calculator

ijtsrd

This paper describes the implementation of electronic scientific calculator using Arduino. The mathematical process for scientific calculation processes are based on the digital electronic technology. The calculator takes input from a user in real time via a keypad and displays output on a LCD display module. The control, arithmetic algorithm and calculation functions are performed using a Arduino Mega 2560. The prototype of the system is configured and the simulation results for basic mathematical functions and some scientific functions of calculator are expressed with the help of Proteus simulation software. And then the experimental results are tested with the constructed calculator circuit. Ma Hnin Yu Myaing | Ma Naing "Arduino Based Scientific Calculator" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26395.pdfPaper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/26395/arduino-based-scientific-calculator/ma-hnin-yu-myaing

Stock Market Analysis and Prediction

Anil Shrestha

This document describes a final year project by four students at Himalaya College of Engineering in Nepal to analyze and predict stock market prices using artificial neural networks. The project aims to develop a neural network model to forecast stock prices on the Nepal Stock Exchange. Various technical, fundamental, and statistical analysis methods are currently used to predict stock prices but with limited success due to the complex nature of financial markets. The project outlines the design of the neural network, selection of input parameters, data collection, model training and testing. The goal is to apply neural networks to help forecast stock prices in Nepal's stock market.

ATI Courses Professional Development Short Course Engineering Systems Modelin...

Jim Jenkins

This two-day course is for engineers, scientists, and others interested in developing custom engineering system models. Principles and practices are established for creating integrated models using Excel and its built-in programming environment, Visual Basic for Applications (VBA). Real-world techniques and tips not found in any other course, book, or other resource are revealed. Step-bystep implementation, instructor-led interactive examples, and integrated participant exercises solidify the concepts introduced. Application examples are demonstrated from the instructor’s experience in unmanned underwater vehicles, LEO spacecraft, cryogenic propulsion systems, aerospace & military power systems, avionics thermal management, and other projects.

Basic Concepts Of Numerical Analysis For Engineering - Edukite

This document describes an online course on basic concepts of numerical analysis for engineering. The course is offered for free through Edukite and introduces students to techniques for numerically solving engineering problems. Topics covered include solving systems of linear equations, roots of equations, differentiation, and integration. To complete the course, students must answer five written assignment questions. Upon completing all assignments, students have the option to pay for an official certificate. The course has been taken by over 600 students and has received positive reviews.

Microsoft excel 2016 intermediate training - Adams Academy

Adams Academy

Since its inception in 1985, Microsoft Excel has an average of five new users added every minute. Now the total stands at more than thirty million users of this amazing spreadsheet program, who use it every day for personal and professional reasons. The 2016 version has many new features added to the program, and if you would like to learn more about them, you can do so with this Microsoft Excel 2016 Intermediate Training course. See more: https://bit.ly/2FWCbC5

Certificate In Analytic Methods In Science And Engineering - Edukite

ASKEDEMYSERIES1BOOK1

ASKBiztechInc

This document describes an online center that provides educational materials for business ERP and MIS skills training. It introduces a series of interactive books and guides that teach applied ERP modules using Business Excel, Project, and Computer Accounting. The books provide step-by-step practical workshops and tutorials to help students and professionals learn skills for using desktop, web-based, and cloud-based ERP applications and tools. The training is administered through an online learning platform that offers study materials, workshops, and certifications.

Microsoft Office 2007 Excel Advanced - Course Gate

This Microsoft Office 2007 Excel Advanced builds on knowledge gained in the Introduction and Intermediate courses. In Advanced Microsoft Office Excel 2007, you will explore the many data analysis tools available in Excel, such as formula auditing, goal seek, Scenario Manager and subtotals. Additionally, during this course you will use advanced functions, learn how to apply conditional formatting, filter and manage your data lists, create and manipulate PivotTables and PivotCharts and record basic macros. See More: https://bit.ly/2GpTkHo

IRJET- Stabilization of Black Cotton Soil using Rice Husk Ash and Lime

This document describes a study that uses machine learning algorithms to predict whether students will be placed in jobs after graduating. The researchers used data on past students' test scores, skills, and placement outcomes to train Naive Bayes and K-Nearest Neighbor classifiers. These algorithms were then used to predict placements for current students based on their profiles. The goal is to help students and institutions focus on improving skills and increasing placement rates, which are important for university reputation. The models use factors like test scores, skills, and course grades to classify students as placed or not placed after training on historical placement data.

IRJET- Student Placement Prediction using Machine Learning

This document describes a study that uses machine learning algorithms to predict whether students will be placed in jobs after graduating. Specifically, it uses Naive Bayes and K-Nearest Neighbors classifiers to analyze historical student data and predict placements. The algorithms consider parameters like academic results, skills, and previous placement data to make predictions. This system aims to help institutions increase placement percentages by identifying students' strengths and areas for improvement. It is intended to benefit both students in preparing for careers and placement cells in targeting support. Accurately predicting placements could boost a school's reputation by demonstrating career outcomes.

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Algorithms and Data Structures - Edukite

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SAP BI Generic Extraction Using a Function Module.pdf

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Arduino Based Scientific Calculator

Stock Market Analysis and Prediction

ATI Courses Professional Development Short Course Engineering Systems Modelin...

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