Document the decision record for AI-based social network analysis so successors understand why it is built this way.
Social Network Analysis Using Artificial Intelligence Algorithms
A structured, applied course in AI-based social network analysis — designed to be used the week you return.
📍 Istanbul🗓️ 5 training days📚 4 modules🎓 Accredited certificate
5intensive training days
4scientific modules
8training sessions
32detailed points
Course Overview
Most organisations now hold more data about AI-based social network analysis than they can actually act on. The distance between a working prototype of network analysis and a system the business can depend on is where most budgets disappear. Content is organised around the decisions practitioners actually face in this area of digital and data-driven work, not around theory headings. Mature organisations treat AI-based social network analysis as a standing capability rather than a project that finishes. The difficulty is not agreeing that this aspect of digital and data-driven work matters — it is deciding what to stop doing to make room for it. Participants who influence network analysis without directly controlling it will find the content directly usable. The programme builds the judgement to know which parts of AI-based social network analysis to standardise and which to leave flexible. The programme uses small-group work so that each participant's treatment of network analysis is examined, not just described. The programme closes with an action plan for the digital and data-driven work capability that each participant writes for their own organisation.
Expected Learning Outcomes
Anticipate the objections that network analysis will attract internally and answer them in advance.
Set retention, lineage and deletion rules for the data flowing through AI-based social network analysis.
Distinguish the parts of network analysis that must be standardised from those that require judgement.
Assess whether AI-based social network analysis should be built in-house, bought, or delivered through a partner.
Plan the migration path for network analysis without an extended outage or a parallel-running trap.
Reduce avoidable variation in how AI-based social network analysis is carried out across teams.
Who Should Attend
Project and programme managers whose delivery depends on AI-based social network analysis.
Chief information officers accountable for the investment in network analysis.
Information security officers reviewing the exposure created by AI-based social network analysis.
Solution architects designing how network analysis fits the existing estate.
Planning staff whose forecasts and budgets are affected by AI-based social network analysis.
Risk and compliance staff assessing the controls around network analysis.
Course Modules
AI-based social network analysis: vendor selection and avoiding lock-in
2 sessions · 8 pointsSession 1The governance AI-based social network analysis needs and the governance it does not
- Draft the minimum viable delivery roadmap for AI-based social network analysis.
- List the data sources network analysis consumes and confirm each has a named owner.
- Confirm the retention and deletion rules applied to data inside AI-based social network analysis.
- Collect evidence on the present handling of network analysis before proposing changes.
Session 2Who answers for network analysis, and to whom
- Reduce the variation in how AI-based social network analysis is carried out between teams.
- Build the user briefing that explains what network analysis does and does not decide.
- Measure the current quality of the data feeding AI-based social network analysis before assuming it is usable.
- Close out actions on network analysis rather than leaving them open indefinitely.
Network analysis: monitoring, drift and operational ownership
2 sessions · 8 pointsSession 1Escalation and decision rights in network analysis
- Establish who is informed, consulted and accountable in AI-based social network analysis.
- Set out the decisions in network analysis that require sign-off and by whom.
- Define the exit route from the supplier supporting AI-based social network analysis.
- Set escalation thresholds for network analysis that work out of hours.
Session 2Explaining network analysis to people whose jobs it changes
- Plan how AI-based social network analysis is versioned and how a bad release is rolled back.
- Agree who is on call for network analysis outside working hours.
- Assess the regulatory obligations AI-based social network analysis triggers in each jurisdiction.
- Build the competence framework that supports network analysis.
Network analysis: architecture, integration and the existing estate
2 sessions · 8 pointsSession 1Where network analysis touches systems nobody wants to change
- Benchmark the organisation's AI-based social network analysis against comparable operations.
- Remove steps in network analysis that add effort without adding assurance.
- Anticipate the objections AI-based social network analysis will raise and prepare the answers.
- Classify the data in network analysis and apply access controls that match the classification.
Session 2The paperwork for AI-based social network analysis that is actually needed
- Test AI-based social network analysis against edge cases drawn from real historical records.
- Identify every system network analysis must read from or write to.
- Define the trigger that would require AI-based social network analysis to be redesigned.
- Decide which legacy process network analysis retires, and set the date.
Network analysis: from pilot to production
2 sessions · 8 pointsSession 1Proving network analysis paid for itself
- Define the service level AI-based social network analysis must meet and what happens when it is missed.
- Identify the skills the team lacks to operate network analysis independently.
- Estimate compute and licensing cost for AI-based social network analysis at expected and at peak load.
- Arrange the handover of network analysis so capability survives staff changes.
Session 2Making network analysis secure without making it unusable
- Prepare the summary of AI-based social network analysis that senior management will read.
- Agree the smallest change to network analysis that would be visibly useful.
- Identify single points of dependency in AI-based social network analysis and reduce them.
- Set the metrics that will show whether network analysis is drifting from its intended behaviour.
Choose the package that suits you
Silver Package
At least 3 people
USD1,250
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Gold Package
At least 3 people
USD1,850
- 5-night stay in a 5-star hotel
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Complete your registration
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