priyavardhini S R
Chennai/Online
About
Priyavardhini S R is a Highly dedicated AI,ML and Data Science Trainer with 6 years of experience in technical education. Her tutoring methodology focuses on project-based learning...
Priyavardhini S R is a Highly dedicated AI,ML and Data Science Trainer with 6 years of experience in technical education. Her tutoring methodology focuses on project-based learning, guiding students through Python, Machine Learning, Deep Learning, and NLP to build real-world applications. I have proven success in structuring modular courses and delivering instructor-led training that accelerates technical proficiency. Key technical competencies include Python libraries, SQL, Google Colab, and Tableau.She is fluent in both English and Tamil, which allows her to connect with a diverse range of students. Priyavardhini focuses on creating a comfortable learning environment where students can ask questions and explore new ideas. Her goal is to inspire confidence and a love for learning in each of her students, whether they are seeking help with specific subjects or looking to strengthen their overall academic skills.
priyavardhini S R
Chennai/Online
Priyavardhini S R is a Highly dedicated AI,ML and Data Science Trainer with 6 years of experience in technical education. Her tutoring methodology focuses on project-based learning...
Priyavardhini S R is a Highly dedicated AI,ML and Data Science Trainer with 6 years of experience in technical education. Her tutoring methodology focuses on project-based learning, guiding students through Python, Machine Learning, Deep Learning, and NLP to build real-world applications. I have proven success in structuring modular courses and delivering instructor-led training that accelerates technical proficiency. Key technical competencies include Python libraries, SQL, Google Colab, and Tableau.She is fluent in both English and Tamil, which allows her to connect with a diverse range of students. Priyavardhini focuses on creating a comfortable learning environment where students can ask questions and explore new ideas. Her goal is to inspire confidence and a love for learning in each of her students, whether they are seeking help with specific subjects or looking to strengthen their overall academic skills.
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Courses by: priyavardhini S R
Artificial Intelligence and Machine Learning - Priyavardhini S R
📌 Module 1: Introduction to AI & Machine Learning
What is Artificial Intelligence?
Types of AI (Weak AI, Strong AI, Super AI)
What is Machine Learning?
Differences between AI, ML & DL
Real-time use cases across industries
📌 Module 2: Python for AI & ML
Python basics & syntax
Variables, loops, functions
Libraries for AI/ML
NumPy
Pandas
Matplotlib
Scikit-learn
Data visualization essentials
📌 Module 3: Data Handling & Preprocessing
Importing datasets
Cleaning and transforming data
Handling missing values
Encoding categorical variables
Feature scaling & selection
Train-test split
📌 Module 4: Core Machine Learning Algorithms
Supervised Learning
Linear & Logistic Regression
Decision Trees & Random Forest
KNN
Naive Bayes
Support Vector Machine
Unsupervised Learning
K-means clustering
Hierarchical clustering
PCA (Dimensionality reduction)
📌 Module 5: Model Evaluation
Confusion matrix
Accuracy, precision, recall
F1 score
ROC & AUC
Overfitting vs underfitting
📌 Module 6: Artificial Intelligence Foundations
Search algorithms (BFS, DFS)
Game playing & heuristics
Intelligent agents
Knowledge representation
Rule-based systems
📌 Module 7: AI with Python
Integrating Python with AI workflows
Building intelligent systems
Automating ML tasks with Python
Introduction to TensorFlow basics
Neural networks overview
📌 Module 8: Mini Projects
Hands-on project experience:
Spam email classifier
Customer segmentation
Movie recommendation system
House price prediction
📌 Module 9: Real-World Industry Applications
AI in healthcare
AI in robotics
AI in finance
AI in e-commerce
AI in automation & IoT
📌 Module 10: Capstone Project
End-to-end AI/ML project including:
Dataset selection
Data preprocessing
Model development
Evaluation metrics
Working demo explanation
