Ai In Education: Master Chatgpt And Prompt Engineering

Reclaim 10+ Weekly Hours | Boost Engagement 65% | Future-Proof Your Career

What you'll learn

Master generative AI and prompt engineering techniques to transform classroom teaching and boost productivity.

Design AI-enhanced lessons, optimize instructional design, and improve student engagement using AI tools like ChatGPT.

Develop AI-powered assessment strategies and grading practices to provide meaningful feedback and personalize learning.

Empower students with AI in the classroom and foster independent learning through innovative AI-driven techniques.

Requirements

No prior AI experience required. This course is designed for complete beginners and provides step-by-step tutorials.

Basic computer skills and access to the internet are necessary to use AI tools and follow along with the course content.

An open mind and willingness to explore new teaching methods and technologies in education.

Description

In today’s AI-driven classrooms, educators who harness generative AI tools gain a 300% productivity advantage.Designed by a Stanford MBA and MA in Education graduate, this course equips teachers with battle-tested ChatGPT strategies to:Reclaim 10+ hours weekly on lesson planning and grading  Boost student engagement by 65% with personalized, AI-driven activities  Future-proof your career with prompt engineering skills 93% of schools now require  What Makes This Different from Other AI Courses?100+ Bite-Sized Videos - Learn efficiently in 3-5 minute chunksReady-to-Use Prompt Templates - Apply strategies in under 5 minutes Learn & Apply Framework - Master a 4-step prompt engineering system Education-Specific - One of few AI courses designed FOR teachersBy Completion, You'll:Transform Teaching: Master generative AI to redesign lessons & boost productivityOptimize Instruction: Create AI-enhanced courses for diverse learning needsRevolutionize Assessment: Develop auto-graded tasks with personalized feedbackEmpower Learners: Foster AI literacy through classroom & independent activitiesCourse StructureModule 1: AI Foundations → Core concepts & ethical considerationsModule 2: Prompt Engineering → Framework for 50+ educational scenariosModule 3: Applied Techniques → Lesson plans, assessments, comms templatesModule 4: Course Design → AI-enhanced curriculum developmentModule 5: Instructional Design → Differentiation & accessibility strategiesModule 6: Engagement Boosters → Gamification & real-world connectionsModule 7: Smart Assessment → Auto-grading & feedback systemsModule 8: Student Empowerment → AI mentors & classroom chatbotsModule 9: Independent Learning → AI study buddies & skill trackersEnroll Now for Just $199.99 – Start Revolutionizing Your Classroom Today!

Overview

Section 1: Course Introduction

Lecture 1 Introduction

Section 2: Module 1: Introduction to generative AI

Lecture 2 1.0: Introduction

Lecture 3 1.1: What is Artificial Intelligence?

Lecture 4 1.2: How does generative AI work?

Lecture 5 1.3: What are Large Language Models (LLMs)?

Lecture 6 1.4: What is ChatGPT?

Lecture 7 1.5: Generative AI for teachers

Lecture 8 1.6: Generative AI for students

Lecture 9 1.7: Capabilities and limitations of generative AI

Lecture 10 1.8: Concerns about AI

Lecture 11 1.9: Ethical use of AI

Lecture 12 1.10: Future of AI

Section 3: Module 2: Introduction to prompt engineering

Lecture 13 2.0: Introduction

Lecture 14 2.1: Getting started with ChatGPT

Lecture 15 2.2: What is prompt engineering?

Lecture 16 2.3: Prompt engineering framework

Lecture 17 2.4: Best practices for writing effective prompts - Part 1

Lecture 18 2.5: Best practices for writing effective prompts - Part 2

Lecture 19 2.6: Persona-based prompts

Lecture 20 2.7: Chain-of-thought prompting

Lecture 21 2.8: Tree of thoughts prompting

Lecture 22 2.9: Rank the prompt

Lecture 23 2.10: What is ChatGPT hallucination?

Section 4: Module 3: Applying prompt engineering techniques

Lecture 24 3.0: Introduction

Lecture 25 3.1: Creating thought-provoking questions

Lecture 26 3.2 Crafting a comprehensive action plan

Lecture 27 3.3: Composing professional emails

Lecture 28 3.4: Chatting with a document

Lecture 29 3.5: Creating a simple budget for your classroom

Lecture 30 3.6: Creating an effective classroom routine

Lecture 31 3.7: Simplifying complex concepts with flowcharts

Lecture 32 3.8: Bringing data to life with charts and graphs

Lecture 33 3.9: Building a PowerPoint presentation

Lecture 34 3.10: Developing a project roadmap

Section 5: Module 4: Designing AI-enhanced lessons and courses

Lecture 35 4.0: Introduction

Lecture 36 4.1: Designing engaging lesson plans

Lecture 37 4.2: Crafting learning objectives and assessments

Lecture 38 4.3: Developing standards-aligned unit plans

Lecture 39 4.4: Implementing project-based learning

Lecture 40 4.5: Integrating technology in classroom instruction

Lecture 41 4.6: Designing cooperative learning activities

Lecture 42 4.7: Creating inclusive lessons

Lecture 43 4.8: Developing personalized learning plans

Lecture 44 4.9: Integrating social-emotional learning in lesson plans

Lecture 45 4.10: Designing interdisciplinary and thematic units

Section 6: Module 5: Optimizing instructional design with AI

Lecture 46 5.0: Introduction

Lecture 47 5.1: Enhancing understanding with multiple examples

Lecture 48 5.2: Crafting multiple explanations for diverse learners

Lecture 49 5.3: Boosting student retention with interleaving practice

Lecture 50 5.4: Simplifying complex concepts

Lecture 51 5.5: Scaffolding reading materials for diverse learners

Lecture 52 5.6: Creating exemplar vs. non-exemplar responses

Lecture 53 5.7: Generating classroom discussion questions

Lecture 54 5.8: Creating discussion questions using Bloom's taxonomy

Lecture 55 5.9: Crafting depth of knowledge-aligned discussion questions

Lecture 56 5.10: Designing custom texts and discussion questions

Section 7: Module 6: Improving student engagement with AI

Lecture 57 6.0: Introduction

Lecture 58 6.1: Connecting classroom concepts to student experiences

Lecture 59 6.2: Bridging classroom concepts with real-world applications

Lecture 60 6.3: Using analogies to make abstract ideas tangible

Lecture 61 6.4: Fostering conceptual understanding with big-picture learning

Lecture 62 6.5: Setting SMART goals for students

Lecture 63 6.6: Creating interactive jeopardy games

Lecture 64 6.7: Designing engaging classroom activities

Lecture 65 6.8: Building vocabulary with AI-curated word lists

Lecture 66 6.9: Applying vocabulary in contextual learning scenarios

Lecture 67 6.10: Developing effective behavior intervention plans

Section 8: Module 7: Enhancing assessment and grading practices with AI

Lecture 68 7.0: Introduction

Lecture 69 7.1: Creating engaging assessments with AI

Lecture 70 7.2: Designing fair and consistent grading practices

Lecture 71 7.3: Building students' confidence with meaningful feedback

Lecture 72 7.4: Empowering students through differentiated assessments

Lecture 73 7.5: Transforming assessments into growth opportunities

Lecture 74 7.6: Designing collaborative assessments that inspire and engage students

Lecture 75 7.7: Personalizing learning paths with student data

Lecture 76 7.8: Using technology to elevate classroom assessments

Lecture 77 7.9: Refining assessment practices for deeper learning

Lecture 78 7.10: Navigating ethical considerations in AI-generated assessment

Section 9: Module 8: Empowering students with AI in the classroom

Lecture 79 8.0: Introduction

Lecture 80 8.1: Tailoring learning experiences with custom chatbots

Lecture 81 8.2: Bringing history to life with AI

Lecture 82 8.3: Mastering the art of debates for engaged learning

Lecture 83 8.4: Guiding students to write with confidence

Lecture 84 8.5: Cultivating creativity in student writing

Lecture 85 8.6: Sparking curiosity in students through Socratic tutoring

Lecture 86 8.7: Fostering critical thinking in STEM challenges

Lecture 87 8.8: Building confidence in programming classrooms

Lecture 88 8.9: Bringing scientific experiments to life

Lecture 89 8.10: Mastering the art of research organization

Section 10: Module 9: Empowering independent learning with AI

Lecture 90 9.0: Introduction

Lecture 91 9.1: Blending the ingredients for dynamic home learning

Lecture 92 9.2: Unlocking student potential through personalized learning plans

Lecture 93 9.3: Transforming blank pages into bold narratives

Lecture 94 9.4: Reimagining language learning for students

Lecture 95 9.5: Mastering the art of debate

Lecture 96 9.6: Streamlining science research for students

Lecture 97 9.7: Cultivating creative and analytical minds

Lecture 98 9.8: Charting a path to future careers

Lecture 99 9.9: Mastering time management

Lecture 100 9.10: Thriving in a tech-driven world

Section 11: Course Conclusion

Lecture 101 Conclusion

Section 12: Final Quiz

K-12 teachers and educators looking to integrate AI into their teaching practices and boost classroom productivity.,Education professionals interested in staying ahead of technological trends and preparing students for an AI-driven future.,School administrators and curriculum designers seeking to implement AI-powered strategies for personalized learning.,Any educator curious about leveraging AI to enhance creativity, save time, and reimagine classroom engagement.