Data Science 30 Days Course easy to learn

About Course

Basic Data Science Course, Step by step learning from zero to hero in just 30 Days

Course Content

Machine Learning in just 30 Days

Day 1: Introduction to Machine Learning and Linear Regression
Day 2: Deep Dive into Logistic Regression
Day 3: Understanding Decision Trees
Assignments for Day 1 to Day 3
Assignment: Linear Regression, Logistic Regression, and Decision Trees
Day 4: Mastering Random Forests
Day 5: Mastering Gradient Boosting
Day 6: Mastering Support Vector Machines (SVM)
Assignments for Day 4 to Day 6
MCQ Assignment for Day 4 to Day 6
Day 7: Mastering K-Nearest Neighbors (KNN)
Day 8: Mastering Naive Bayes Algorithm
Day 9: Mastering Principal Component Analysis (PCA)
Assignments for Day 7 to Day 9
MCQ Assignment for Day 7 to Day 9
Day 10: Mastering k-Means Clustering
Day 11: Mastering Hierarchical Clustering
Day 12: Mastering Association Rule Learning
Assignments for Day 10 to Day 12
Day 13: Mastering DBSCAN (Density-Based Spatial Clustering of Applications with Noise)
Day 14: Mastering Linear Discriminant Analysis (LDA)
Day 15: Mastering XGBoost (Extreme Gradient Boosting)
Day 16: Mastering LightGBM (Light Gradient Boosting Machine)
Day 17: Mastering CatBoost (Categorical Boosting)
Day 18: Mastering Neural Networks
Day 19: Mastering Convolutional Neural Networks (CNNs)
Day 20: Mastering Recurrent Neural Networks (RNNs)
Day 21: Mastering Long Short-Term Memory (LSTM)
Day 22: Mastering Gated Recurrent Units (GRUs)
Day 23: Mastering Autoencoders
Day 24: Mastering Generative Adversarial Networks (GANs)
Day 25: Mastering Transfer Learning
Day 26: Mastering Ensemble Learning
Day 27: Mastering Natural Language Processing (NLP)
Day 28: Mastering Time Series Analysis and Forecasting
Day 29: Mastering Model Deployment and Monitoring
Day 30: Mastering Hyperparameter Optimization
Comprehensive Capstone Project
MCQ Assignment for Day 10 to Day 12

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