AI-Powered Customer Experience
AI-Powered Customer Experience is a intermediate-level, 3 Weeks online course by NSTC. Master key concepts and practical skills in Artificial Intelligence through hands-on projects, real-world case studies, and expert mentorship.
- ModeOnline (e-LMS)
- LevelIntermediate
- Duration3 Weeks
- Fee₹4,249
| Attribute | Detail |
|---|---|
| Format | Online (e-LMS) |
| Level | Intermediate |
| Duration | 3 Weeks |
| Certification | e-Certification + e-Marksheet |
| Fee | ₹4249 / $56 |
| Tools | Python TensorFlow PyTorch Keras Scikit-learn Jupyter Notebook Google Colab Hugging Face |
About the AI-Powered Customer Experience Course
AI-powered Customer Experience: Enhancing Engagement and Satisfaction is an 8-week course designed for M.Tech, M.Sc, and MCA students, as well as E0 & E1 level professionals in IT and related sectors.
The course covers the use of AI in customer service chatbots, recommendation systems, sentiment analysis, and more, providing participants with practical skills and theoretical knowledge to implement AI-driven enhancements in customer experience.
Program Highlights
• Comprehensive coverage of Powered Customer Experience from fundamentals to advanced applications
• Hands-on projects and real-world case studies in Artificial Intelligence
• Expert-curated curriculum aligned with current industry standards
• Access to recorded lectures and e-LMS platform for flexible, self-paced learning
• e-Certification and e-Marksheet upon successful completion
• Dedicated mentor support and interactive doubt-clearing sessions
• Exposure to industry-standard tools and platforms used in Artificial Intelligence
• Career-oriented training for academic and professional growth in Artificial Intelligence
Course Curriculum
Module 1: Introduction to AI in Customer Experience
- Section 1.1: Understanding AI Basics
- Section 1.2: Overview of Customer Experience (CX)
- Section 1.3: The Intersection of AI and CX
- Section 1.4: Current Trends and Future Predictions
Module 2: Tools and Technologies
- Section 2.1: Key AI Technologies in CX
- Section 2.2: Platforms and Tools Overview
- Section 2.3: Integrating AI Tools into Existing Systems
- Section 2.4: Case Studies: Successes and Failures
Module 3: Data Management and Analytics
- Section 3.1: Data Collection Methods
- Section 3.2: Data Analysis Techniques
- Section 3.3: Generating Insights from Customer Data
- Section 3.4: Privacy and Ethical Considerations
Module 4: Personalization Strategies
- Section 4.1: Understanding Customer Behavior
- Section 4.2: AI-driven Personalization Techniques
- Section 4.3: Implementing Personalization at Scale
- Section 4.4: Evaluating Personalization Effectiveness
Module 5: Enhancing Customer Interactions
- Section 5.1: Chatbots and Virtual Assistants
- Section 5.2: AI in Customer Support
- Section 5.3: Real-time Problem Solving with AI
- Section 5.4: Feedback and Continuous Improvement
