User:Saroj Neupane Lesson Plan 6

From ICTED-WIKI
Jump to navigation Jump to search

Subject : Computer Science

Period: 3rd

Topic: Machine Learning and its Applications

School: ABC School

Class: 10

Unit: Seven

Time: 15 min

No. of Students: 20

Specific Objectives[edit | edit source]

  • At the end of the class students will be  able to understand   key concepts, types of ML, and real-world applications.

Teaching Materials[edit | edit source]

  • Whiteboard and markers or a digital presentation tool
  • Projector or screen (if using digital presentation)

Teaching Learning Activities (10 minutes)[edit | edit source]

  • Start with a question: "How do you think computers can learn and make decisions without being explicitly programmed?" Encourage students to share their thoughts.
Applications of ML
  • Provide a concise definition: "Machine Learning is a subset of artificial intelligence where computers learn patterns from data to make predictions or decisions without explicit programming."
  • Arthur Samuel first used the term "machine learning" in 1959.
  • Introduce key types of machine learning:
  1. Supervised Learning: Learning from labeled data with input-output pairs.
  2. Unsupervised Learning: Learning from unlabeled data to find patterns.
  3. Reinforcement Learning: Learning through trial and error with a reward-based system.
  • Discuss fundamental concepts:
  1. Training Data: The dataset used to train the machine learning model.
  2. Algorithms: Mathematical models that learn patterns from data.
  3. Features: Input variables used by the model to make predictions.
  4. Predictions: The output generated by the machine learning model.
How Machine Learning works?
  • Describe how machine learning works?
  • Discuss on applications of Machine Learning.

Case Study or Example (2 minutes):[edit | edit source]

  • Share a brief case study or example that illustrates how machine learning is applied in a specific industry or scenario. Use visuals or a short video clip if available.

Conclusion and Q&A (1 minute)[edit | edit source]

  • Summarize the key points discussed in the lesson.
  • Open the floor for questions from students.

Assessment (2 minutes)[edit | edit source]

A. Multiple choice questions

  

1 What is machine Learning?

A type of computer virus
A branch of artificial intelligence
A programming language
A hardware component

2 Which term is used to describe the dataset used to train a machine learning model?

Test Data
Input Data
Training Data
Output Data

3 In Supervised Learning, what is the role of labeled data?

To test the model's performance
To train the model
To validate the model
To ignore the model

4 Which of the following is a real-world application of Machine Learning?

Building a website
Sorting files on a computer
Fraud detection in financial transactions
Sending emails

B. What are the applications of Machine learning?


Optional Activity (if time allows)[edit | edit source]

Conclude with a brief interactive activity, such as asking students to brainstorm potential applications of machine learning in their daily lives.