Saurabh Jondhale
Online
About :
Saurabh Jondhale is dedicated to helping students understand complex concepts in a clear and engaging way. He focuses on creating a supportive learning environment where students f…
Saurabh Jondhale is dedicated to helping students understand complex concepts in a clear and engaging way. He focuses on creating a supportive learning environment where students feel comfortable asking questions. Saurabh communicates effectively in English, ensuring that his teaching is accessible to all learners. His approach emphasizes clarity and practical understanding, making it easier for students to grasp subjects and achieve their academic goals.
Saurabh Jondhale
Online
Saurabh Jondhale is dedicated to helping students understand complex concepts in a clear and engaging way. He focuses on creating a supportive learning environment where students f...
Saurabh Jondhale is dedicated to helping students understand complex concepts in a clear and engaging way. He focuses on creating a supportive learning environment where students feel comfortable asking questions. Saurabh communicates effectively in English, ensuring that his teaching is accessible to all learners. His approach emphasizes clarity and practical understanding, making it easier for students to grasp subjects and achieve their academic goals.
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Courses by Saurabh Jondhale
Online
30 Hour
English
Pune, Western Avenue
On Call
Weekend
What You Will Learn
This course covers the basics of Artificial Intelligence (AI) and Machine Learning (ML). You will learn key concepts step by step. The course consists of several modules, each focusing on different aspects of AI and ML.
Module 1: Introduction to AI & ML
Understand what AI and Machine Learning are.
Learn the differences between AI, ML, Deep Learning, and Data Science.
Explore real-world applications of AI.
Discover types of Machine Learning: Supervised, Unsupervised, and Reinforcement Learning.
Get an overview of the AI workflow.
Module 2: Python for AI/ML
Learn Python basics such as variables, data types, loops, and functions.
Explore libraries like NumPy, Pandas, and Matplotlib.
Practice coding exercises and loading datasets.
Module 3: Math for ML
Understand mean, median, mode, and standard deviation.
Learn basics of probability and correlation.
Get an introduction to gradient descent.
Module 4: Data Preprocessing
Learn how to clean data and handle missing values.
Understand how to handle duplicates and encode categorical data.
Explore feature scaling and train-test split.
Get an introduction to feature engineering.
Module 5: Supervised Machine Learning
Learn about regression techniques: Linear and Multiple Regression.
Understand classification methods: Logistic Regression, Decision Trees, Random Forest, and KNN.
Module 6: Model Evaluation
Learn how to evaluate models using accuracy, precision, recall, and F1 score.
Understand the confusion matrix and concepts of overfitting and underfitting.
Module 7: Unsupervised Learning
Discover K-Means Clustering and PCA basics.
Learn about customer segmentation.
Module 8: Intro to Deep Learning
Understand the basics of neural networks and perceptrons.
Learn about activation functions and get an overview of TensorFlow/Keras.
Module 9: Mini Project
Choose a project like House Price Predictor, Spam Classifier, or Customer Segmentation.
You will practice using tools like Python, Jupyter Notebook, NumPy, Pandas, Matplotlib, Scikit-learn, and TensorFlow throughout the course.