Having a strong background in the fundamentals of AI/ML is crucial for building real-world applications that automate and optimize your lifestyle. Artificial Intelligence and Machine Learning precisely describe how to train our application to learn from the data, analyze it, and gain decisive abilities. 

Lesson 1: Introduction to Artificial Intelligence and Machine Learning

• What is AI? What is ML? Differences between AI, ML, DL, and Data Science
• Real-world applications
• History and evolution of AI
• Types of ML: Supervised, Unsupervised, Reinforcement Learning
• Tools setup: Python, Jupyter Notebooks, Google Colab

Lesson 2: Python for AI/ML

• Python basics recap: variables, data types, functions, control flow
• Libraries for ML: NumPy, pandas, matplotlib
• Hands-on with data loading, preprocessing, and visualization

Lesson 3: Mathematics for ML - Part 1

• Linear Algebra essentials: vectors, matrices, dot product
• Applications in ML
• Numpy-based matrix operations

Lesson 4: Mathematics for ML - Part 2

• Probability and Statistics basics
• Mean, median, variance, standard deviation
• Distributions, correlation vs. causation

Lesson 5: Supervised Learning - Regression

• Linear regression (Simple and Multiple)
• Cost function, gradient descent
• Evaluation metrics: MAE, MSE, RMSE, R² score
• Hands-on: House price prediction dataset

Lesson 6: Supervised Learning - Classification

• Logistic regression
• Decision trees
• Confusion matrix, accuracy, precision, recall, F1 score
• Hands-on: Email spam classifier

Lesson 7: Unsupervised Learning - Clustering

• K-means clustering
• Evaluation: Elbow method, silhouette score
• Hands-on: Customer segmentation

Lesson 8: Unsupervised Learning - Dimensionality Reduction

• Principal Component Analysis (PCA)
• Feature selection vs. extraction
• Hands-on: Visualizing high-dimensional data

Lesson 9: Model Evaluation and Tuning

• Train/test/validation split
• Cross-validation
• Hyperparameter tuning (Grid Search, Random Search)
• Avoiding overfitting/underfitting

Lesson 10: Introduction to Deep Learning

• What is Deep Learning? Neural Networks
• Perceptron, forward/backward propagation
• Brief intro to TensorFlow/Keras or PyTorch

Lesson 11: Capstone Project Work

• Students form groups or work individually
• Choose a dataset, define a problem, build and evaluate a model
• Instructor mentorship

Lesson 12: Project Presentations + Wrap-Up

• Students present their projects
• Peer review
• Course recap, next steps, career guidance, resources

How to identify words and the parts of speech they belong to.

Lesson 1:  Introduction to Nouns

• Definition of nouns and their role in sentences.
• Types: Common vs. Proper, Singular vs. Plural, Concrete vs. Abstract.
• Types: Common vs. Proper, Singular vs. Plural, Concrete vs. Abstract.

Lesson 2:  Nouns in Action

• Possessive nouns, collective nouns, countable vs. uncountable nouns.
• How nouns function as subjects and objects in sentences.
• Activity: Writing descriptive sentences using different types of nouns.

Lesson 3:  Introduction to Pronouns

• Definition and purpose of pronouns.
• Types: Personal, Subject vs. Object Pronouns.
• Activity: Pronoun substitution exercises (replacing nouns with pronouns).

Lesson 4:  Pronouns in Action

• Possessive, reflexive, and demonstrative pronouns.
• Pronoun-antecedent agreement to avoid confusion.
• Activity: Editing sentences to correct pronoun errors.

Lesson 5: Introduction to Verbs

• Definition and role of verbs in sentences.
• Types: Action vs. Linking Verbs.
• Activity: Identify and act out action verbs (interactive game).

Lesson 6: Verbs in Action

• Helping verbs, modal verbs, and irregular verbs.
• Subject-verb agreement rules.
• Activity: Sentence-building with verbs in different tenses.

Lesson 7: Introduction to Adjectives

• Definition and function of adjectives.
• Types: Descriptive, Demonstrative, Proper Adjectives.
• Activity: "Describe the Picture" – Using adjectives to describe objects.

Lesson 8: Adjectives in Action

• Comparative and superlative adjectives (bigger, biggest).
• Adjective order in sentences (size, color, origin).
• Activity: Rearranging adjectives in the correct order in sentences.

Lesson 9: Introduction to Adverbs

• Definition and function of adverbs.
• Types: Adverbs of Manner, Place, Time, Frequency.
• Activity: Match verbs with appropriate adverbs (e.g., "run quickly").

Lesson 10: Adverbs in Action

• Comparative and superlative adverbs (well → better → best).
• Avoiding overuse of adverbs in writing.
• Activity: Rewrite weak sentences by replacing or removing unnecessary adverbs.

Lesson 11: Introduction to Prepositions

• Definition and function of prepositions.
• Types: Prepositions of Place, Time, and Movement.
• Activity: Preposition hunt – finding prepositions in a short passage.

Lesson 12: Prepositions in Action

• Prepositional phrases and their role in sentences.
• Common preposition errors (in/on, at/by).
• Activity: Writing short descriptions using prepositions.

Lesson 13: Introduction to Conjunctions

• Definition and function of conjunctions.
• Types: Coordinating Conjunctions (FANBOYS: For, And, Nor, But, Or, Yet, So).
• Activity: Sentence-combining exercises using FANBOYS.

Lesson 14: Conjunctions in Action

• Subordinating conjunctions (because, although, while).
• Correlative conjunctions (either/or, neither/nor).
• Activity: Writing complex sentences using different conjunctions.

Lesson 15: Introduction to Interjections

• Definition and function of interjections.
• Types: Strong vs. Mild Interjections (Wow! Oops! Oh…).
• Activity: Identifying interjections in comics and everyday speech.

Lesson 16: Interjections in Action

• How interjections add emotion to writing and speech.
• Formal vs. informal interjections.
• Activity: Role-playing short dialogues using interjections.

Overview:
Learn core web technologies to build responsive, interactive websites. Perfect for beginners!

What You’ll Learn:

• HTML5: Page structure, forms, accessibility
• CSS3: Layouts (Flexbox/Grid), animations, responsive design
• JavaScript: DOM manipulation, events, ES6+ features
• Bonus: Git basics, deployment, DevTools
• Outcome: Build real projects and prepare for advanced frameworks.

Why Enroll? Hands-on projects, Beginner-Friendly, Industry-Ready Skills