Artificial Intelligence and Algorithms in Journalism

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Introduction

Good morning, everyone. Welcome to the training course on Artificial Intelligence and Algorithms in Journalism.

This course is designed to bring you up to speed on the concepts, tools, and techniques related to AI and algorithms that are being used in modern journalistic practices. We will explore how these technologies can be leveraged to create stories with more accuracy, greater insight, and a bigger impact.

You will also learn about the ethical considerations that come with creating and using algorithms for journalism purposes.

By the end of this course, you should have a better understanding of what AI means for journalism today and how it can help us tell stories more effectively in the future.

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Introduction

Good morning, everyone. Welcome to the training course on Artificial Intelligence and Algorithms in Journalism.

This course is designed to bring you up to speed on the concepts, tools, and techniques related to AI and algorithms that are being used in modern journalistic practices. We will explore how these technologies can be leveraged to create stories with more accuracy, greater insight, and a bigger impact.

You will also learn about the ethical considerations that come with creating and using algorithms for journalism purposes.

By the end of this course, you should have a better understanding of what AI means for journalism today and how it can help us tell stories more effectively in the future.

 

Objectives

  1. Understand the fundamentals of Artificial Intelligence (AI) and Algorithms in Journalism, including their applications and implications for the industry.
  2. Learn how to implement AI technologies into journalism projects and practice data analysis and visualization techniques.
  3. Develop an understanding of ethical, legal, and regulatory implications of using AI systems in newsrooms.
  4. Acquire skills to investigate the implications of algorithms on media storytelling and journalistic practices.
  5. Gain knowledge of relevant software tools used in artificial intelligence and algorithmic approaches in journalism.

 

Course Outline

Module 1: Introduction to Artificial Intelligence and Algorithms in Journalism

-Define AI and algorithms and their components

-Understand the role of AI and algorithms in journalism

– Fundamentals of Artificial Intelligence (AI) and Algorithms in Journalism, including their applications and implications for the industry.

-The history of AI and algorithmic systems in journalism

-Types of AI applications used in journalism

-Advantages and disadvantages of using AI algorithms for automated reporting

– Using cases for automated journalism by major news organizations around the world

 

 Module 2: Developing Automated Reporting with Algorithms 

-Learn how to design an algorithm for automated reporting

– How to implement AI technologies into journalism projects and practice data analysis and visualization techniques

-Gain understanding of data sources that can be used in automated journalism

-Practical examples on developing automated news using algorithms such as Python, R, Java, SAS etc.

-Database Management Systems like SQL, MongoDB etc. required for storing data wisely while working with algorithmic approaches to reporting

-How to collect relevant data from various sources including web scraping techniques

-Data cleansing techniques like Outlier Detection and Data Imputation.

-Practice creating a basic algorithm from scratch based on real world examples.

-How to create a simple web scraper or crawler that can extract useful information from different websites for your project.

 

Module 3: Supervised Learning & Natural Language Processing (NLP) For Automated Reporting

-Understand supervised learning models for automated reporting

-Learn about popular NLP techniques utilized today in automation

-Machine learning models like Regression, Decision Trees, Naïve Bayes etc.

-Different methods of performing classification tasks

-Natural Language Processing topics such as sentiment analysis, syntax analysis & automatic summarization Activities

–Developing a model specific to detecting fake news using different supervised learning models       –Implementing a sentiment classifier using NLP concepts

 

Module 4: Deep Learning & Reinforcement Learning Techniques for Automated Reporting

–Understanding deep neural networks & its underlying principles

–Grasp reinforcement learning fundamentals & its various applications

–Deep Neural Networks (DNNs) such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs).

–Reinforcement Learning topics such as Qlearning, Temporal Difference Methods.

–Applications of these techniques studied through existing examples.

–demonstrate Implementation of CNN classifier model which helps categorize different type of articles or posts

–Designing Reinforcement Learning environment where unmanned vehicles/agents can learn optimal path towards achieving some tasks.

– understanding of ethical, legal, and regulatory implications of using AI systems in newsrooms.

– Skills to investigate the implications of algorithms on media storytelling and journalistic practices.

– Gain knowledge of relevant software tools used in artificial intelligence and algorithmic approaches in journalism.

 

Module 5: Exams and Certification

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