Machine Learning(DEC-2025)
Machine Learning Subject official course #Batch: December 2025 to May 2026
₹2500.00 ₹3000.00 17% OFF
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Course Overview
Machine Learning Subject official course #Batch: December 2025 to May 2026
Schedule of Classes
Start Date & End Date
Dec 24 2025 - May 31 2026
Course Curriculum
1 Subject
Machine Learning(DEC-2025)
42 Learning Materials
Machine Learning Notes
UNIT 1 INTRODUCTION TO MACHINE LEARNING
UNIT-2 DATA PREPROCESSING
UNIT-III Feature Selection
UNIT-IV Supervised Learning
UNIT-V Unsupervised Learning
Unit - I Introduction to Machine Learning
08 Jan Lecture-1
12 Jan Lecture-2
13 Jan Lecture-3
19 Jan Lecture-1 : Define Machine Learning, How it works
20 Jan Lecture-2 :Types of Machine Learning
21 Jan Lecture-3 : Application of ML, Challenges in ML and Python with ML
Unit-II Data Preprocessing
22 Jan Lecture-1 Data Cleaning :Introduction to Data Cleaning, Identifying and Handling Noisy Data
23 Jan Lecture-2: Removing Duplicates, Standardizing and Normalizing Data, Handling Outliers
24 Jan Lecture-3 Types of Missing Data, Identifying Missing Values, Techniques
25 Jan Lecture-4 THandle Missing Data, Removing Missing Data, Mean, Median, and Mode Imputation
UNIT-II Lecture-5 Splitting Dataset for Training and Testing
UNIT-II Lecture-6
UNIT-II Lecture-7
UNIT-III Feature Selection
16 Feb Lecture-1 Feature Selection, Feature Scaling
17 Feb Lecture-2 Importance of Feature Scaling, PCA
20 Feb Lecture-3 Differentiate between Standardization and Normalization, Feature Selection Methods
21 Feb Lecture-4 PCA and LDA, Mutual Information, Feature Extraction Techniques
22 Feb Lecture-5 ANOVA, RFECV, Random Forest
23 Feb Lecture-6 XGBoost and LightGBM, Gini Importance and SHAP Values
UNIT-IV Supervised Learning
24 Feb Lecture-1 Supervised Learning, Linear Regression
26 Feb Lecture-2 Difference between Classification and Linear Regression, SVM
27 Feb Lecture-3 Linear Regression, Logistic Regression, Decision Trees
28 Feb Lecture-4 model evaluation techniques, Confusion Matrix, Diff between Precision and Recall
01 March Lecture-5 Decision Boundary in SVM, Ridge Regression
02 March Lecture-6 Decision Tree, List and explain types of regression algorithms
03 March Lecture-7 KNN Algorithm
UNIT-V Unsupervised Learning
UNIT-V Lecture-1 Unsupervised Learning concept and its example
UNIT-V Lecture-2 Clustering,List applications of clustering, importance of clustering
UNIT-V Lecture-3 K-means clustering, Hierarchical Clustering
12 March Lecture-4
13 March Lecture-5
Revision Lectures
21 March Lecture-1 Revision of UNIT-III
23 March Lecture-2 Revision of UNIT-III
24 March Lecture-3 Revision of UNIT-III
25 March Lecture-4 Revision of UNIT-IV
28 March Lecture-5 Revision of UNIT-IV
29 March Lecture-6 Revision of UNIT-IV
Course Instructor
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VJTech Academy
23 Courses • 19261 Students
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