Insights & Market Research in 2027 – Scenario ThinkingRay Poynter
This presentation by Ray Poynter forms part of the New Thinking in Insights - Asia Pacific Event hosted by NewMR.org.
To listen to the recording, please access via NewMR.org/play-agan.
Description:
Predictions tend to go wrong and the recognised alternative is based on scenario thinking. In this presentation Ray Poynter highlights the key trends that are happening at the moment and develops an analysis of what the insights and market research outlook might offer.
Guide PV d'AG : tout savoir sur l'organisation d'une Assemblée GénéraleCaptain Contrat
Dans notre guide sur le PV d'AG, vous découvrirez toutes les étapes de l'organisation d'une Assemblée Générale, ordinaire ou extraordinaire.
Pourquoi préparer une AG ? Comment rédiger un Procès-Verbal, et par qui ? Quelles sont toutes les formalités liées ?
Toutes les réponses se trouvent dans notre guide entier du PV d'AG.
Using a public dataset of images of maritime vessels provided by Analytics Vidhya, manual annotations were made on a subsample of images with Roboflow using the ground truth classifications provided by the dataset. YOLOv5, a prominent open source family of object detection models that comes with an out-of-the-box pre-training on the Common Objects in Context (COCO) dataset, was used to train on annotations of subclassifications of maritime vessels. YOLOv5 provides significant results in detecting a boat. The training, validation, and test set of images trained YOLOv5 in the cloud using Google Colab. Three of our five subclasses, namely, cruise ships, ROROs (Roll On Roll Off, typically car carriers), and military ships, have very distinct shapes and features and yielded positive results. Two of our subclasses, namely, the tanker and cargo ship, have similar characteristics when the cargo ship is unloaded and not carrying any cargo containers. This yielded interesting misclassifications that could be improved in future work. Our trained model resulted in the validation metric of mean Average Precision (mAP@.5) of 0.932 across all subclassification of ships.
Insights & Market Research in 2027 – Scenario ThinkingRay Poynter
This presentation by Ray Poynter forms part of the New Thinking in Insights - Asia Pacific Event hosted by NewMR.org.
To listen to the recording, please access via NewMR.org/play-agan.
Description:
Predictions tend to go wrong and the recognised alternative is based on scenario thinking. In this presentation Ray Poynter highlights the key trends that are happening at the moment and develops an analysis of what the insights and market research outlook might offer.
Guide PV d'AG : tout savoir sur l'organisation d'une Assemblée GénéraleCaptain Contrat
Dans notre guide sur le PV d'AG, vous découvrirez toutes les étapes de l'organisation d'une Assemblée Générale, ordinaire ou extraordinaire.
Pourquoi préparer une AG ? Comment rédiger un Procès-Verbal, et par qui ? Quelles sont toutes les formalités liées ?
Toutes les réponses se trouvent dans notre guide entier du PV d'AG.
Using a public dataset of images of maritime vessels provided by Analytics Vidhya, manual annotations were made on a subsample of images with Roboflow using the ground truth classifications provided by the dataset. YOLOv5, a prominent open source family of object detection models that comes with an out-of-the-box pre-training on the Common Objects in Context (COCO) dataset, was used to train on annotations of subclassifications of maritime vessels. YOLOv5 provides significant results in detecting a boat. The training, validation, and test set of images trained YOLOv5 in the cloud using Google Colab. Three of our five subclasses, namely, cruise ships, ROROs (Roll On Roll Off, typically car carriers), and military ships, have very distinct shapes and features and yielded positive results. Two of our subclasses, namely, the tanker and cargo ship, have similar characteristics when the cargo ship is unloaded and not carrying any cargo containers. This yielded interesting misclassifications that could be improved in future work. Our trained model resulted in the validation metric of mean Average Precision (mAP@.5) of 0.932 across all subclassification of ships.
Les réseaux de neurones convolutifs CNNSALMARACHIDI1
La présentation a débuté par une introduction aux Réseaux de Neurones Convolutifs (CNN), en soulignant leur importance croissante dans le domaine de l'intelligence artificielle et du traitement d'images. Les CNN sont particulièrement adaptés à la reconnaissance d'images, à la classification d'objets et à d'autres tâches liées à la vision par ordinateur.
La première partie de la présentation a abordé les fondements des CNN. Les participants ont été familiarisés avec les concepts de base des réseaux de neurones et ont pu comprendre les différences entre les réseaux de neurones classiques et les CNN. Un accent particulier a été mis sur l'architecture spécifique des CNN, comprenant des couches de convolution, des couches de pooling et des couches entièrement connectées. Les participants ont compris comment les opérations de convolution permettent d'extraire des caractéristiques importantes des images, tandis que les opérations de pooling réduisent la dimensionnalité et conservent les informations essentielles.
Dans la deuxième partie de la présentation, l'accent a été mis sur l'implémentation pratique des CNN en utilisant le langage de programmation Python. Les participants ont été guidés à travers les étapes de construction d'un modèle CNN en utilisant des bibliothèques populaires telles que TensorFlow ou PyTorch. Ils ont appris à définir les couches de convolution, les couches de pooling et les couches entièrement connectées, ainsi qu'à configurer les hyperparamètres du modèle.
La présentation a également abordé des sujets connexes tels que l'entraînement et l'évaluation des modèles CNN, l'application de la technique de transfert d'apprentissage pour des tâches spécifiques, et les défis liés à la mise à l'échelle des CNN pour des ensembles de données plus volumineux.
En résumé, la présentation sur les Réseaux de Neurones Convolutifs (CNN) a permis aux participants de comprendre les principes fondamentaux de cette architecture, ainsi que d'acquérir les connaissances nécessaires pour mettre en œuvre un modèle CNN en utilisant Python. Ils ont également été sensibilisés aux applications et aux perspectives futures des CNN dans le domaine de la vision par ordinateur.
DeepVO - Towards Visual Odometry with Deep LearningJacky Liu
Author:
Sen Wang1,2, Ronald Clark2, Hongkai Wen2 and Niki Trigoni2
1. Edinburgh Centre for Robotics, Heriot-Watt University, UK
2. University of Oxford, UK
Download this paper: http://senwang.gitlab.io/DeepVO/#paper
Watch video: http://senwang.gitlab.io/DeepVO/#video
(주)인사이트컨설팅 대표이사 고명환입니다.
예비창업자 & 창업자 대상 맞춤형 강의안입니다.
창업보육센터, 소상공인, 대학생 등 수차례 강의를 수행하였습니다.
- Business Model Canvas?
- Examples
- Start Workshop
- PT&토론하기
http://blog.naver.com/maru7091
Automatic attendance system has two stages: Face recognition and face detection. Though there are many efficient algorithms for frontal face detection and recognition when large pose comes into picture most of the developed algorithm fails to detect. Here in this presentation I used two state-of-the-art results to make an automatic attendance system.
Les réseaux de neurones convolutifs CNNSALMARACHIDI1
La présentation a débuté par une introduction aux Réseaux de Neurones Convolutifs (CNN), en soulignant leur importance croissante dans le domaine de l'intelligence artificielle et du traitement d'images. Les CNN sont particulièrement adaptés à la reconnaissance d'images, à la classification d'objets et à d'autres tâches liées à la vision par ordinateur.
La première partie de la présentation a abordé les fondements des CNN. Les participants ont été familiarisés avec les concepts de base des réseaux de neurones et ont pu comprendre les différences entre les réseaux de neurones classiques et les CNN. Un accent particulier a été mis sur l'architecture spécifique des CNN, comprenant des couches de convolution, des couches de pooling et des couches entièrement connectées. Les participants ont compris comment les opérations de convolution permettent d'extraire des caractéristiques importantes des images, tandis que les opérations de pooling réduisent la dimensionnalité et conservent les informations essentielles.
Dans la deuxième partie de la présentation, l'accent a été mis sur l'implémentation pratique des CNN en utilisant le langage de programmation Python. Les participants ont été guidés à travers les étapes de construction d'un modèle CNN en utilisant des bibliothèques populaires telles que TensorFlow ou PyTorch. Ils ont appris à définir les couches de convolution, les couches de pooling et les couches entièrement connectées, ainsi qu'à configurer les hyperparamètres du modèle.
La présentation a également abordé des sujets connexes tels que l'entraînement et l'évaluation des modèles CNN, l'application de la technique de transfert d'apprentissage pour des tâches spécifiques, et les défis liés à la mise à l'échelle des CNN pour des ensembles de données plus volumineux.
En résumé, la présentation sur les Réseaux de Neurones Convolutifs (CNN) a permis aux participants de comprendre les principes fondamentaux de cette architecture, ainsi que d'acquérir les connaissances nécessaires pour mettre en œuvre un modèle CNN en utilisant Python. Ils ont également été sensibilisés aux applications et aux perspectives futures des CNN dans le domaine de la vision par ordinateur.
DeepVO - Towards Visual Odometry with Deep LearningJacky Liu
Author:
Sen Wang1,2, Ronald Clark2, Hongkai Wen2 and Niki Trigoni2
1. Edinburgh Centre for Robotics, Heriot-Watt University, UK
2. University of Oxford, UK
Download this paper: http://senwang.gitlab.io/DeepVO/#paper
Watch video: http://senwang.gitlab.io/DeepVO/#video
(주)인사이트컨설팅 대표이사 고명환입니다.
예비창업자 & 창업자 대상 맞춤형 강의안입니다.
창업보육센터, 소상공인, 대학생 등 수차례 강의를 수행하였습니다.
- Business Model Canvas?
- Examples
- Start Workshop
- PT&토론하기
http://blog.naver.com/maru7091
Automatic attendance system has two stages: Face recognition and face detection. Though there are many efficient algorithms for frontal face detection and recognition when large pose comes into picture most of the developed algorithm fails to detect. Here in this presentation I used two state-of-the-art results to make an automatic attendance system.
Oracle Cloud Platform Update, showing Cloud in Action from an Oracle IAAS, PAAS Perspective, including Mobile and Application Development Perspectives.
For Video Snippets
https://www.youtube.com/watch?v=qBZX7v5X2aM&list=PL4kFVH3YjCInfgFAlT9gvPKatpC4Xjm5D
For Event Details
https://solutionsanz.blog/2017/02/28/speed-2-value-cloud-in-action-workshop/
Every Women and girl want fit physique but only some of them can able to achieve their goals. So in this ppt we are going to share the important and top 10 fitness tips for women. Follow the mentioned fitness tips for women in order to get best results.
Building on the blog post http://tech.transferwise.com/we-inspire-smart-people-and-we-trust-them/ these slides which were presented at the big data summit, walk through a little of how we structure our teams around KPIs to drive growth.
Instagram Analytics: What to Measure to Grow Your InstagramPeg Fitzpatrick
I’ve spend the past few months testing the top tools for Instagram analytics. If you’re interested in growing your Instagram account, you’ll learn what the top features are for these tools and which tools will work best for you. I encourage you to test them and find the one that meets your needs best. http://pegfitzpatrick.com/instagram-analytics/
Автоматизация SEO-задач в 2017 — CyberMarketing — СевальневДмитрий Севальнев
Подробней: https://tools.pixelplus.ru и http://www.pixelplus.ru/samostoyatelno/
Тезисы:
- Какие работы по SEO можно и нельзя автоматизировать?
- Группы задач в SEO: семантика, распределение, технический аудит, внутренняя и внешняя оптимизация, анализ конкурентов и выдачи, снятие санкций, поведенческие метрики, отчетность.
- Основные сервисы автоматизации на рынке.
- Плюсы и минусы автоматизации.
- Выводы и полезные ссылки.
1
ACC ACF 2400 – Semester 2, 2017
Individual Assignment 1:
Building a Business Dashboard
Overview
A business dashboard is ‘a style of reporting that depicts KPIs, operational or strategic information with
intuitive and interactive displays’ (Turban et al., 2015 p. 380). It is a single screen snapshot of how a
business, department, or process is performing. The design varies considerably from one application
to another, and even between businesses, but a common feature of a dashboard is that it uses graphs,
coloured text, and symbols to show the viewer, at a glance, the current status. A dashboard should
only contain information that actually influences performance. Many dashboards are interactive
because it can be difficult to show every important detail at once.
You are an employee at Australian Electronics Pty Ltd. You have been assigned the task of designing
a report that will be used by managers involved in purchasing, sales, and inventory management.
Your boss, Mary Smith, suggest including at least four (4) ratios. Regarding the ratios, Mary thinks
that Inventory Turnover and Sales Growth are a must.
This is an individual assignment. There is no fixed answer, so be creative!! The spreadsheet must
perform ratio analysis to show the current status of the inventory holdings and sales. Marks are
awarded according to how well the dashboard meets the requirements specified in the rubric.
A data set is supplied with this guide in Moodle (ACC ACF 2400_s2 2017_Inventory Statistics.xlsx). The
Inventory Statistics data set contains four sheets: sales value, sales quantity, the quantity of inventory
on hand, and the quantity purchased. You should use all sheets in your calculations, but may need to
restructure some data on a separate calculation sheet to ensure data is in the format you need.
Instructions on how to build a complex interactive scorecard have been published in different journals
such as the Journal of Accountancy
(http://www.journalofaccountancy.com/issues/2011/feb/20092427.html), but you do not have to
build such a complex system if your spreadsheeting skills are not well developed.
The table below contrasts two different approaches. The example on the left shows 7 ratios in a non-
interactive dashboard, with three graphs and one table of numbers. It is clearly not an inventory
management dashboard, but if the design features included were tailored to the inventory
management context, it would likely earn a pass (providing instructions, the input sheet, and the
calculations sheet are acceptable).
The example on the right, however, is from the Dashboard your Scorecard article. It is also not an
inventory management dashboard and does not show ratios, and so is not acceptable, but illustrates
elements that will earn higher marks:
• It is interactive (note the drop-down box in the bottom right graph to select the person shown);
• It uses conditional for ...
The Art of Data Visualization in Microsoft Excel for Mac.pdfTEWMAGAZINE
As more people turn to the internet and electronic gadgets for their source of information, you can expect data to increase exponentially daily. Data is a result of sharing, collecting, and transmitting information.
Bing Ads' Eric Couch dives in to beginning and advanced Excel tips and tricks for PPC marketers- including data analysis tips, Excel formulas, and incredibly handy plugins.
$5 COUPON LINK - Excel Udemy Course: Excel with Excel Dynamic Graphs, Dashboa...mellontraining
Learn everything about Charts with Excel 2013
Create Interactive Advanced Excel Charts, Pivot Charts and Dashboards - with Microsoft Excel 2013 + Free Excel Templates
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GET THE COURSE FOR $5 WITH THE COUPON LINK:
https://www.udemy.com/excel-charts-learn-everything-about-charts-with-excel-2013/?couponCode=STUDENT5
1 Analytics Group Project Instructions OBJEC.docxtarifarmarie
1
Analytics Group Project Instructions
OBJECTIVE:
Your objective is to evaluate a company’s processes, develop an integrated accounting database,
produce a simple set of financial reports, and conduct analyses that will add value and enhance the
performance of the company. Ideally, groups will have 3-4 members. You may work with your group in-
person and/or online.
Carefully read the description of Boneless Seafood company. Become familiar with the data contained
in the associated Boneless Seafood Excel data file. Review the instructions below and discuss the
project with your group before you begin work. Although you will divide up the workload, every
student should be familiar with every part of the project. Each aspect should be discussed and agreed
upon, and all members are responsible for producing an integrated final project.
What you’ll turn in:
In class:
Printed report that contains an executive summary, table of contents, and items described in
deliverables A through H. Further details are provided on p. 3 and in subsequent instructions.
One combined, sequential time log that shows dates, activities, and names of group member or
members who completed each activity. You can use a shared Google sheet or any format of your
choice to track your progress.
In my email:
Subject line: 335 HB1 Group Project: Amy Lee, Pat Garcia, and Joe Smith (use your own section
and names)
3 attachments: A single Access database that includes properly numbered and descriptively named
queries, a summary Excel file, and a single Word or PDF document that contains your entire report
(use a scanner or scanning app such as Genius Scan if necessary).
**Important** I change some aspects of my projects each term. If a group submits answers to a
previous term’s assignment, the group will receive a 0 on the project and will be subject to a hearing by
the university’s academic integrity disciplinary committee. You’re investing a lot of time and money to
learn accounting—do your own work so that you can get the knowledge and skills you’re here for.
Keep copies of all of your notes and preliminary work in case you need to provide evidence of the
independence of your work or of your contribution to the group effort.
Suggestions for how to get started
Before you begin, study the instructions, interviews, and data.
Complete part B first, and make sure everyone understands and agrees on the data
model. Chapter 8 provides a lot of information that might be helpful as you work through the group
project. For example, Figure 8.6 provides a generic data model you can use as a starting point.
Each table in the Excel file will represent an entity in your model, except that the orders_sales file will
need to be broken into its heading and line items components (to see why, look at Atla_O90007.) You
may break down some other event files as well.
2
The table below gives s.
Dashboards can contain an a lot of critical data. How much is too much? Evaluate your business needs and goals to determine what is the right data and what is too much content.
Bound Tech is the Top Institute For Tableau training. Tableau Hands On Training and Tableau Job Oriented Training is taught by Our Real Time Trainer with real time scenario’s and examples. We teach our students from the fundamental concepts to the highly developed concepts.
Tableau is one of the fastest evolving Business Intelligence (BI) and data visualization tool. It is very quick to deploy, easy to learn and very spontaneous to use for a customer. It has evolved into one of the fastest and easiest way to share analytics in the cloud.
Part 1 - Microsoft AccessView GlossaryUse Access to create a.docxhoney690131
Part 1 - Microsoft Access
View Glossary
Use Access to create a database in which you can store and retrieve information about the Rio Salado Theme Park operating departments, their managers, and their employees.
Create a
new blank database
.
Save the database with the filename
RSC_Theme_Park_Database_MEID.accdb
. Replace “MEID” with your actual MEID.
Structure of the Database
NOTE:
Read the requirements for the database and be sure you understand how it should work before creating your design.
You will need to complete the following:
Create two tables.
Establish table relationships.
Create one form.
Create two queries.
Create one report.
As you work on the project, remember to follow best practices for creating databases as described in your TestOut materials and the online lesson content.
Create the Tables
Tables and their relationships form the backbone of a relational database. In this database, you will create a table for the Rio Salado Theme Park operating departments and their managers, and a table for employees in each department. When creating fields for your tables, it is important to break down your data into the smallest chunks you can (fine granularity) to make it easier to extract data from the database later. Remember to assign the most appropriate data type to each of the fields and that one of the fields in each of your tables must be set as the
Primary Key
using the
AutoNumber
data type. You do not need to enter data records into your tables at this time; you will create a form later in this project for data entry.
Department Table
Create a
table
named
Department Table
. At a minimum, your table should include the following fields:
Department ID
Department Name
Manager First Name
Manager Last Name
Manager Email Address
Manager Phone Number
Employee Table
Create a
table
named
Employee Table
. At a minimum, your table should include the following fields:
Employee ID
Department ID
Employee First Name
Employee Last Name
Employee Date of Hire
Employee Rate of Pay
Establish Table Relationships
Once the design of the tables has been completed, the next step is to
establish relationships
between the tables. You will join the Department Table with the Employee Table on common fields through the following tasks:
Join the
primary key
of the Department Table with the
foreign key
of the Employee Table in a
One-To-Many
relationship.
Enforce referential integrity.
Cascade update related fields.
Cascade delete related records.
Create a Form
Once the tables have been designed and the relationships have been established, it is time to enter data. You will use
one form
to enter and edit data in the two tables:
Create
one form
named
Department Form
that can be used to enter data into both tables.
Insert a row
below the Employee Table subform. Add a
button
in the new row to perform the
Add New Record
action with the text:
Add Record
.
Use the form to enter
a m.
These slides provide detailed instructions on a fast, easy and effective way to map, evaluate and find actions to improve your job, your team members’ jobs, or ANY job.
A slide deck on "Why Map Your Job!" can be found at
https://howtomapyourjob.com/slides/why
Map That Job! Core Training Slides NEWER (AND BETTER) VERSION at howtomapyou...Jim Johnson
These slides provide detailed instructions on a fast, easy and effective way to map, evaluate and find actions to improve your job, your team members’ jobs, or ANY job.
NEWER (AND BETTER) VERSION at howtomapyourjob.com/slides/coretraining
A slide deck on "Why Map That Job!" can be found at
https://mapthatjob.com/slides/why
WK8_A2 OverviewAssignment 2 Excelling with ExcelDue Week 8 an.docxambersalomon88660
WK8_A2 Overview
Assignment 2: Excelling with Excel
Due Week 8 and worth 175 points
Overview
Microsoft Excel is a great tool for presenting, organizing, and calculating data. It can be used to create budgets, track your weekly spending, or create detailed plans. This assignment will give you an opportunity to crunch the numbers on your most recent school supply purchases.
Assignment Requirement:
To successfully complete this assignment, submit this (1) Microsoft Excel sheet that includes the following information and formatting.
Steps:
1. Complete the steps listed in the "WK8_A2_Instructions" sheet.
2. Save your document with the following name – CIS105_Assignment2_FirstName_Last Name.xlsx
3. Submit your assignment in Week 8.
Recommended TestOut Desktop Pro Skills Labs to review prior to completing this assignment are:
3.2.4 Skills Lab: Create and Manage Workbooks
3.3.5 Skills Lab: Organize and Enter Data
3.5.6 Skills Lab: Format Cells
3.6.4 Skills Lab: Enter Simple Formulas
3.8.4 Skills Lab: Analyze Data in Charts
Recommended Lynda.com Videos to Watch
Microsoft Excel 2013
Lynda.com Video: Excel 2013 Essential Training
URL: https://www.lynda.com/Excel-tutorials/Excel-2013-Essential-Training/116478-2.html
Microsoft Excel 2016
Lynda.com Video: Excel 2016 Essential Training
URL: https://www.lynda.com/Excel-tutorials/Excel-2016-Essential-Training/376985-2.html
Excel for Mac 2011
Lynda.com Video: Excel for Mac 2011 Essential Training
URL: https://www.lynda.com/Excel-2011-for-mac-tutorials/essential-training/71210-2.html
Excel for Mac 2016
Lynda.com Video: Excel for Mac 2016 Essential Training
URL: https://www.lynda.com/Excel-tutorials/Excel-Mac-2016-Essential-Training/159244-2.html
WK8_A2_Instructions
Instructions for Saving a File
You will be using this file to complete this assignment, so remember to save your changes as you go along.
Hint: When saving this workbook for the first time, Microsoft Excel saves the document in a default location. To save the document in a different location, click another folder or location in the Save As dialog box.
1. Click File, and then click Save As.
2. Save using the file name - CIS105_Assignment2_FirstName_Last Name_Date.xlsx.
3. Click Save.
Instructions to Complete Week 8 Assignment 2
Use this workbook to write down and calculate the costs of the school materials you purchased for this quarter. Consider the following materials you needed for your course work (i.e., use the stated amounts below regardless of the actual items / costs you may have purchased / paid):
First, in the Title Page worksheet, enter the following information.
Type your name in cell B1.
Type in the course section you are in cell B2. (For example: CIS105111)
Type your professor’s name in cell B3.
Type the title of the assignment in cell B4. (The title is “Excelling with Excel”)
Rename the worksheet to "Overview."
Change the font type for this information to Century Gothic.
Change the .
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
2. Purna Duggirala Chief Excel Officer Chandoo.org SESSION CODE: ##### Selecting Right Chart for your Data
3. Today we will, Why it is important to select the right chart? How to make the right chart? Some really cool ideas to play with
4. Why is it important? Source: http://www.perceptualedge.com/articles/Whitepapers/Communicating_Numbers.pdf
5. Why is it important? Right chart Right decision vs. Source: http://www.perceptualedge.com/articles/Whitepapers/Communicating_Numbers.pdf
6. Why is it important? Right chart Faster Interpretation
7. How to make the right chart? Step 1: Identify what you want to say Step 2: (Re)arrange your data accordingly Step 3: Prepare the chart Step 4: Remove distracting elements, format
8. How to make the right chart? Step 1: Identify what you want to say Step 2: (Re)arrange your data accordingly Step 3: Prepare the chart Step 4: Remove distracting elements, format
9. What do you want to say? Ask yourself What is the message?
10. Common Messages in Business Comparison Trend over time Distribution Deviation Parts to Whole Relationship
11. Common Messages in Business Comparison Trend over time Distribution Deviation Parts to Whole Relationship
12. Common Messages in Business Comparison Trend over time Distribution Deviation Parts to Whole Relationship
13. Common Messages in Business Comparison Trend over time Distribution Deviation Parts to Whole Relationship
14. Common Messages in Business Comparison Trend over time Distribution Deviation Parts to Whole Relationship
15. Common Messages in Business Comparison Trend over time Distribution Deviation Parts to Whole Relationship
16. Common Messages in Business Comparison Trend over time Distribution Deviation Parts to Whole Relationship
17. How to make the right chart? Step 1: Identify what you want to say Step 2: (Re)arrange your data accordingly Step 3: Prepare the chart Step 4: Remove distracting elements, format
19. How to make the right chart? Step 1: Identify what you want to say Step 2: (Re)arrange your data accordingly Step 3: Prepare the chart Step 4: Remove distracting elements, format
26. Charts for Your Message Message Charts Applicable Relationship
27. How to make the right chart? Step 1: Identify what you want to say Step 2: (Re)arrange your data accordingly Step 3: Prepare the chart Step 4: Remove distracting elements, format
28. Format the Chart No non-zero axis scale on bar charts Make subtle gridlines (or remove them) Add labels to important points Add descriptive, bold titles Position axis, scales at the right places Use simple, easy colors
34. Some cool tools to help you Juice Analytics Chart Chooser http://chartchooser.juiceanalytics.com/ BonaVista Chart Tamer Excel Add-in http://chandoo.org/wp/2009/05/04/review-chart-tamer/
35. More Information and Techniques http://chandoo.org/wp/tag/charting-principles/ http://peltiertech.com/Excel/Charts/index.html http://www.perceptualedge.com/library.php#Articles http://www.excelcharts.com/blog/category/popular/