Online/ e-LMS
Self Paced
Moderate
3 Weeks
About
Participants will explore how AI tools like natural language processing (NLP) and machine learning can be applied to social media data. The program covers techniques for understanding sentiment, detecting trends, predicting virality, and creating strategies for social media optimization.
Aim
To equip participants with advanced skills to analyze and interpret data from social media platforms using AI technologies. This program will cover sentiment analysis, trend detection, and the use of AI for understanding user behavior and engagement on social platforms.
Program Objectives
- Understand how AI can be applied to analyze social media data.
- Master sentiment analysis and trend detection using AI.
- Learn how to optimize social media strategies based on user engagement.
- Gain insights into visual content analysis using AI tools.
- Build a real-time social media analysis project.
Program Structure
- Introduction to AI in Social Media
- Overview of social media data sources and types
- Importance of AI in understanding and analyzing social media data
- Natural Language Processing (NLP) for Social Media
- Text processing techniques for sentiment and emotion analysis
- Real-time sentiment analysis using AI tools
- Trend Detection and Social Listening with AI
- Using AI for real-time trend detection and analysis
- Predicting virality and social media trends using machine learning
- Social Media Engagement Analytics
- AI techniques for analyzing user behavior and engagement
- Tools to measure and improve social media ROI
- AI for Image and Video Analysis in Social Media
- Understanding visual content trends using AI
- Image recognition and video analysis techniques
- Hands-On Project: Social Media Sentiment and Trend Analysis
- Building a sentiment analysis and trend detection system using Python
- Analyzing real-time data from platforms like Twitter and Instagram
Participant’s Eligibility
Social media marketers, data scientists, digital strategists, and AI professionals focusing on social platforms.
Program Outcomes
- Proficiency in using AI to analyze and predict social media trends.
- Expertise in sentiment analysis and user engagement optimization.
- Ability to develop AI tools for real-time social media monitoring.
- Hands-on experience in building AI-powered social media solutions.
Fee Structure
Standard Fee: INR 4,998 USD 78
Discounted Fee: INR 2499 USD 39
We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!
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Live
Certificate
Program Assessment
Certification to this program will be based on the evaluation of following assignment (s)/ examinations:
| Exam | Weightage |
|---|---|
| Mid Term Assignments | 50 % |
| Project Report Submission (Includes Mandatory Paper Publication) | 50 % |
To study the printed/online course material, submit and clear, the mid term assignments, project work/research study (in completion of project work/research study, a final report must be submitted) and the online examination, you are allotted a 1-month period. You will be awarded a certificate, only after successful completion/ and clearance of all the aforesaid assignment(s) and examinations.
Program Deliverables
- Access to e-LMS
- Real Time Project for Dissertation
- Project Guidance
- Paper Publication Opportunity
- Self Assessment
- Final Examination
- e-Certification
- e-Marksheet
Future Career Prospects
- Social Media Data Analyst
- AI Social Media Strategist
- Social Media Marketing Analyst
- Digital Content Analyst
- Trend Analyst for Social Media Platforms
- Social Media Sentiment Analyst
Job Opportunities
- Social media platforms and digital marketing agencies requiring AI-powered analytics.
- Media companies looking to analyze social engagement and content performance.
- Brands implementing AI tools to measure and predict user behavior on social media.
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Recent Feedbacks In Other Workshops
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the workshop was very good, thank you very much
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