Centram Centre for Applied Artificial Intelligence

AI , ANALYTICS AND AUTOMATION COURSE FOR PUBLIC RELATIONS

Course overview

This course is designed for public relations (PR) professionals who want to use AI, analytics and automation to improve media monitoring, content creation, campaign measurement and crisis response. It emphasizes real-world workflows, ethical safeguards and hands-on labs using both no-code tools and light-code options.

Course title

AI, Analytics & Automation for Public Relations

Course description

This practical course empowers PR professionals how to apply AI, analytics and automation across the PR lifecycle: media monitoring and social listening, sentiment and topic analysis, influencer identification, automated reporting and dashboards, AI-assisted content creation and distribution, paid-media optimization, and crisis detection/response. Covers tools and workflows (no-code and code-light), model governance and ethics. Strong emphasis on labs and a capstone PR automation project.

Target audience

PR managers, Communications officers, Media Relations Specialists, Digital Strategists, Content Producers.

This course has 2 deliver modes: 2-week intensive physical boot camp training plus 3 weeks of online training OR 4 weeks of intensive boot camp training

Learning objectives

By the end of the course participants will be able to:

  1. Design and run automated media monitoring and social listening pipelines.
  2. Use NLP techniques to detect sentiment, topics, named entities and emerging issues.
  3. Build dashboards and automated reports that measure PR outcomes and attribution.
  4. Apply generative AI responsibly to draft content, press materials and social posts with human-in-the-loop checks.
  5. Identify and prioritize influencers and stakeholder segments using analytics.
  6. Automate routine PR workflows (press list updates, press release distribution, reporting).
  7. Implement basic campaign optimization using analytics and automation
  8. Recognize legal and ethical risks (privacy, bias, misinformation, deepfakes) and design governance controls.

Course content

Orientation & PR use cases

  1. Typical AI automation opportunities: 24/7 media monitoring, sentiment tracking, influencer identification, automated reporting, content drafting, crisis alerts.
  2. Course roadmap, datasets, tools, capstone options, quick demo of an automated monitoring → alert pipeline.

AI & analytics fundamentals for PR

  1. Key concepts: supervised vs unsupervised learning, embedding, classification, clustering, evaluation metrics (precision/recall/AUC, nDCG for ranking).
    1. Data sources & quality: APIs, RSS, press wires, social media, web scraping, media databases; privacy considerations.

Media monitoring & social listening pipelines

  1. Architecting ingestion: sources, connectors (Twitter/X API, Facebook/Meta, Instagram, Reddit, news APIs, RSS, Meltwater/Brandwatch connectors).
  2. Deduplication, entity resolution, storage (Elasticsearch, AWS/GCP buckets).
  3. Lab: build a simple ingestion pipeline and index articles/posts.

NLP for PR: sentiment, topic & entity analysis

  1. Text pre-processing, sentiment analysis (VADER, transformer models), topic modeling (LDA, BERTopic), NER, entity linking to organizations/people.
  2. Lab: run sentiment & topic analysis on a press dataset; produce a media sentiment timeline.

Emerging issue detection & crisis monitoring

  • Early-warning signals: anomaly detection, sudden volume spikes, sentiment shift, cluster emergence.
  • Setting thresholds, human escalation rules, automated alerting and playbooks.
  • Lab: implement alert rules that trigger Slack/email notifications and produce a sample crisis playbook.

Influencer & stakeholder analytics

  1.  Metrics for influence: reach, engagement, audience overlap, topical authority, network centrality.
  2. Social graph basics and influencer scoring; authenticity/fraud detection (bots/fake accounts).
  3. Lab: identify and rank influencers for a campaign using social API data and network metrics.

Automated measurement & dashboards

  1.  KPIs: share of voice, sentiment, message pull-through, media placements, earned/impressions, referral traffic and conversion metrics.
  2. Building dashboards and automated reporting (Tableau, Power BI, Google Data Studio, or dashboards from Data Studio + scheduled emails).
  3. Lab: build an automated weekly PR dashboard with drilldowns and scheduled distribution.

Generative AI for content & creative workflows

  1.  Use cases and limits: drafting press releases, social copy variants, Q&As, media pitches, boilerplate creation.
  2. Human-in-the-loop workflows, prompt design, hallucination mitigation, brand voice control, editing checklist.
  3. Lab: design a workflow to generate multiple copy variants, run guardrails, and integrate approval steps before publishing.

 Campaign optimization & paid-media automation

  1. Attribution basics for PR-driven outcomes (UTM tagging, multi-touch attribution, uplift testing).
  2. Automating A/B tests for copy and distribution windows; using analytics for spend allocation and boost decisions.
  3. Lab: simulate simple campaign optimization loop using engagement and conversion metrics; create rules for auto-boosting top-performing posts.

Automation & RPA for PR workflows

  1. Automating routine tasks: press list maintenance, clipping reports distribution, follow-up reminders, media outreach triggers.
  2. Tools: Zapier, Make.com, Power Automate, social schedulers (Hootsuite/Buffer), newsroom APIs.
  3. Lab: build an automation that converts monitoring hits into CRM/press-list entries and schedules follow-ups.

Ethics, legal, governance & crisis simulations

  1.  Privacy (GDPR), platform policies, copyright, disclosure requirements (sponsored content/paid placements), handling deepfakes and misinformation.
  2.  Documentation: model cards, datasheets, audit trails, escalation paths.
  3.  Lab: run a tabletop crisis simulation using your monitoring pipeline + scripted deepfake/misinformation scenario; exercise governance checklist.

          Capstone project presentations & roadmaps

  1.  Teams present capstone projects (see ideas below), deployment considerations and handover documentation.
  2. Peer review and instructor feedback, implementation roadmap for organizational pilots.
  3. Capstone project ideas (team or individual)
    – Real-time media monitoring + alerting system for a brand with automated triage and escalation playbook.
  4.  Influencer identification and outreach automation with scoring, templated pitches (AI-drafted) and follow-up tracking.
  5. Automated PR reporting product: ingest coverage, run sentiment & topic analysis, produce scheduled executive brief and media clippings.
  6. AI-assisted press release generation with A/B testing of headlines + auto-scheduling and performance measurement.
  7. Crisis simulation tool that detects anomalies and generates suggested responses and stakeholder messages.

Hands-on labs)

  • Building an ingestion + Elasticsearch index for news + tweets.
  • Running sentiment & topic modeling; produce executive one-page brief automatically.
  • Creating an influencer scoring notebook and export a press-list CSV.
  • Building and scheduling an automated weekly dashboard emailed to stakeholders.
  • Implementing an alert rule and integrate it with Slack + create a sample escalation email.

Tools and platforms (no-code → code-light)

  1. Monitoring & social tools: Brandwatch, Meltwater, Sprout Social, Hootsuite (concepts + API examples).
  2. APIs and ingestion: Twitter/X API, Reddit API, NewsAPI, MediaCloud, RSS, web scraping with BeautifulSoup/Scrapy (code labs optional).
  3. NLP & ML: Python (pandas), spaCy, Hugging Face transformers, VADER/TextBlob, BERTopic, scikit-learn.
  4. Indexing & search: Elasticsearch/OpenSearch, vector similarity (sentence-transformers + FAISS).
  5. Automation: Zapier, Make.com, Power Automate, social schedulers (Buffer/Hootsuite) and CRM integrations.
  6. Dashboards & reporting: Tableau, Power BI, Google Data Studio, or simple Jupyter/Streamlit dashboards.

Deployment & collaboration: Slack/email integrations, Zapier, Cloud functions (AWS Lambda/GCP Cloud Functions) for scheduled jobs.