9. HR management (Curriculum)

Human Resource Management - the activities associated with recruiting,development, and compensation of employees.

9.1. Some rules to help you run your company

• Remove rules

• Be candid with each others

• Hire adults

• Hire best people you can

• Give freedom

• Give responsibility

9.2. .NET Curriculum

9.2.1. Documentation

• sphinx : https://www.sphinx-doc.org/en/master/usage/restructuredtext/basics.html

  1. install sphinx

  2. install template rtfd

Todo

3. create a public repo on github presenting a template for sphinx projects

9.2.2. Testing

• Creating Unit Tests for ASP.NET MVC Applications (C#) :

  • https://docs.microsoft.com/en-us/aspnet/mvc/overview/older-versions-1/unit-testing/creating-unit-tests-for-asp-net-mvc-applications-cs

• Testing and debuggin ASP.NET Web API :

  • Testing and Debugging ASP.NET Web API

• SeleniumHQ Browser automation :

  • https://www.seleniumhq.org

• End to end testing angular :

  • https://www.protractortest.org

9.2.3. Software engineering

• The Joel Test - 12 Steps to Better Code

• The Joel Test For Programmers (The Simple Programmer Test)

9.2.4. Software development .NET

• Microsoft .NET : C#

• Debugging code back-end (Visual Studio)

• Debugging code front-end (Browser, Visual Studio)

• Debugging code on Azure (Browser, Visual Studio)

• MVC : ASP.NET MVC Model-View-Controller

• CSS : https://developer.mozilla.org/en-US/docs/Web/CSS

• Bootstrap 4 : https://getbootstrap.com/

• Authentication/Authorization: .net identity

• REST API: securization by token containing a UUID + Claims. Log using MS Account -> Get VSTS tokens -> display Personal projects

• REST API (documentation/deployment): SWAGGER

• REST API (test) : POSTMAN

• SPA Single Page Application

  • ANGULAR

    • Linter : https://angular.io/cli/lint

  • Typescript

    • Linter : https://github.com/Microsoft/dtslint

• NUGET: back-end code + database + migration database + INL/Metis repository

9.2.5. DATA MODELING .NET and Azure

• Entity framework: Code first

• Database:

  • SQL (SQL Server), Azure SQL Server classic (do not use elastic pool)

  • NoSQL: CosmosDB

• File storage (SMB 3.0)

• Media (photo, video, sound): Azure Media services

9.2.6. GENERATE OFFICE FILES

• File Format APIs : https://www.aspose.com

9.2.7. DEPLOYMENT

• Team Services: Understand the agile methodology

• Azure Web App : https://portal.azure.com

• Azure Pipelines : https://azure.microsoft.com/en-us/services/devops/pipelines

• Jenkins supports building, deploying and automating any project.: https://jenkins.io/

9.2.8. Artificial intelligence / Machine learning / Big data analysis

• Artificial intelligence: https://azure.microsoft.com/en-us/services/cognitive-services

• Machine learning: https://azure.microsoft.com/en-us/services/machine-learning-services

• NTLK Natural Language Toolkit : https://www.nltk.org

9.2.9. Reproducible research

• Tools

  • Jupyter notebook are documents produced by the Jupyter Notebook App, which contain both computer code (e.g. python) and rich text elements (paragraph, equations, figures, links, etc): http://jupyter.org

  • nteract and create with data, words, and visuals : https://nteract.io/

  • Microsoft Azure Notebooks : http://notebooks.azure.com

  • Colabotary : https://colab.research.google.com/

• Theory

  • Reproducable research: https://mg.readthedocs.io/reproducible_research.html

  • Reproducibility Workshop: Best practices and easy steps to save time for yourself and other researchers: https://codeocean.com/workshop/caltech

9.3. Excel Curriculum

9.3.1. Lookups

• Introduction

• VLOOKUP

• VLOOKUP Exact Match

• HLOOKUP

• HLOOKUP Exact Match

9.3.2. Conditional Logic

• Introduction

• IF Statement

• Nested IF

• AND

• OR

• NOT

• IFERROR

• SUMIF

• AVERAGEIF

• COUNTIF & COUNTIF

• SUMIFS

• AVERAGEIFS

9.3.3. Data Tools

• Introduction

• Data Validation

• Drop-Down Lists

• Removing Duplicates

• Text To Columns

• Goal Seek

• Scenario Manager

9.3.4. PivotTables

• Introduction

• Creating PivotTables

• Choosing Fields

• PivotTable Layout

• Filtering PivotTables

• Modifying PivotTable Data

• PivotCharts

9.3.5. Collaboration

• Introduction

• Document Properties

• Inserting Hyperlinks

• Sharing a Workbook

• Track Changes

• Accept/Reject Changes

• Mark as Final

9.3.6. Printing

• Introduction

• Page Orientation

• Page Breaks

• Print Area

• Margins

• Print Titles

• Headers and Footers

• Scaling

• Sheet Options

9.3.7. Macros

• Introduction and Macro Security

• Recording a Macro

• Assign a Macro to a Button or Shape

• Run a Macro upon Opening a Workbook

• How to Inspect and Modify a Macro

9.4. Secure and Private Artificial Intelligence

• course source :

  • https://classroom.udacity.com/courses/ud185

  • other course : https://www.udacity.com/school-of-ai

9.4.1. Deep learning with PyTorch

• https://research.fb.com/category/facebook-ai-research

• Notebooks : https://github.com/udacity/deep-learning-v2-pytorch

9.4.1.1. Install Python3

• create a python3.7.X environment : conda create -n py37 python=3.7 anaconda

• activate the environment conda activate py37

• deactivate the environment conda deactivate

• determining my environment : conda info –envs

9.4.1.2. Install PyTorch an Conda

• Install Conda

  • install Anaconda : https://docs.anaconda.com/anaconda/install and https://conda.io/en/latest

  • or install Miniconda : https://docs.conda.io/en/latest/miniconda.html

  • Some commands

    • managing environments : https://conda.io/projects/conda/en/latest/user-guide/getting-started.html#managing-environments

    • example of commands : conda search scipy, conda install scipy, conda build my_fun_package, conda update conda

• Install PyTorch https://pytorch.org/get-started/locally

  • for old GPU (does not work on Geforce GT 520M conda install pytorch torchvision cudatoolkit=9.0 -c pytorch -c defaults -c numba/label/dev

  • conda install pytorch torchvision cudatoolkit=10.0 -c pytorch

• Install numpy, jupyter and notebook

  • conda install numpy jupyter notebook

9.4.1.3. Launching Jupyter Notebook App

• jupyter notebook - https://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/execute.html

9.4.2. Udacity course : Deep Learning with PyTorch

This repo contains notebooks and related code for Udacity’s Deep Learning with PyTorch lesson. This lesson appears in our [AI Programming with Python Nanodegree program](https://www.udacity.com/course/ai-programming-python-nanodegree–nd089).

• Part 1: Introduction to PyTorch and using tensors

• Part 2: Building fully-connected neural networks with PyTorch

• Part 3: How to train a fully-connected network with backpropagation on MNIST

• Part 4: Exercise - train a neural network on Fashion-MNIST

• Part 5: Using a trained network for making predictions and validating networks

• Part 6: How to save and load trained models

• Part 7: Load image data with torchvision, also data augmentation

• Part 8: Use transfer learning to train a state-of-the-art image classifier for dogs and cats

9.4.3. Tools for Artificial Intelligence

• Gym is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents everything from walking to playing games like Pong or Pinball. https://gym.openai.com

• ONNX is an open format to represent deep learning models. With ONNX, AI developers can more easily move models between state-of-the-art tools and choose the combination that is best for them. ONNX is developed and supported by a community of partners. https://onnx.ai

• Machine learning cheatsheet : https://ml-cheatsheet.readthedocs.io