Machine Learning Track

Machine Learning:
Level-01

Name: Machine Learning Course Level 1 - Fundamentals
Availability: InStock

4.8 (1,230 reviews)

Introduction to Machine Learning: Level-01. Develop skills in model tuning, feature engineering, and using tools like scikit-learn and TensorFlow for predictive analytics.

Created by Avanteia

12,580 Total Enrolled

15 September 2024 Last Updated

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2 Months Duration

Certificate On Completion

Introduction

Overview

Develop skills in model tuning, feature engineering, and using tools like scikit-learn and TensorFlow for predictive analytics.

Python ML Statistics Scikit-learn Preprocessing TensorFlow

Goal

Learning Outcome

Develop more sophisticated machine learning models, optimize algorithms for better performance, and gain experience with neural networks and data management techniques.

Curriculum

Syllabus

Click any module to expand and view topics and hands-on labs included.

What is ML? Types (Supervised, Unsupervised, Reinforcement)
ML vs AI vs Deep Learning
Real-world applications
ML workflow & pipeline

Hands-on Lab

Install Python & Jupyter/Colab Run a basic ML pipeline on Iris dataset in Scikit-learn

Python essentials (functions, OOP, file handling)
NumPy, Pandas for data manipulation
Matplotlib, Seaborn for visualization

Hands-on Lab

Load CSV dataset in Pandas Perform summary statistics Plot graphs using Matplotlib/Seaborn

Data cleaning (missing values, outliers)
Categorical encoding (One-hot, Label Encoding)
Scaling (MinMax, StandardScaler)
Feature selection & extraction

Hands-on Lab

Handle missing values in Titanic dataset Apply feature scaling on dataset in Scikit-learn

Probability basics, Bayes Theorem
Distributions (Normal, Bernoulli, Binomial, Poisson)
Hypothesis testing (t-test, chi-square)

Hands-on Lab

Simulate coin toss & dice using Python Test significance using SciPy

Linear Regression, Multiple Regression
Polynomial Regression
Regularization (Lasso, Ridge)

Hands-on Lab

Predict house prices using Linear Regression (Kaggle dataset) Compare Ridge vs Lasso regression

Logistic Regression
k-Nearest Neighbors (k-NN)
Decision Trees
Support Vector Machines (SVM)

Hands-on Lab

Predict Titanic survival (Logistic Regression) Build k-NN classifier on Iris dataset

Random Forest, Gradient Boosting, XGBoost
Bagging vs Boosting vs Stacking
Hyperparameter tuning (GridSearchCV, RandomSearchCV)

Hands-on Lab

Use Random Forest on loan prediction dataset Perform hyperparameter tuning with GridSearch

k-Means Clustering
Hierarchical Clustering
PCA & Dimensionality Reduction

Hands-on Lab

Perform customer segmentation using K-Means (Retail dataset) Apply PCA on Wine dataset

Results

What You Will Learn

Regression & Classification

Build and evaluate Linear, Polynomial, Logistic Regression, k-NN, Decision Trees, and SVM models.

Ensemble Methods

Master Random Forest, Gradient Boosting, XGBoost, and apply hyperparameter tuning for optimal performance.

Feature Engineering

Apply advanced data preprocessing, feature selection, and scaling techniques for robust ML pipelines.

Unsupervised Learning

Implement clustering algorithms and dimensionality reduction for pattern discovery and data visualization.

Testimonials

What Our Students Say

The Level 2 course took my skills to a professional level. The Active Directory labs and privilege escalation modules are exactly what I needed to land my first pentesting job. Avanteia's hands-on approach is unmatched.

Vikram Patil Penetration Tester, Mumbai

I completed the Beginner course first and immediately enrolled in Intermediate. The malware analysis and reverse engineering modules were eye-opening. The 2-month duration is perfect for working professionals.

Sneha Kadam Cybersecurity Analyst, Pune

The cloud security and wireless hacking modules are incredibly relevant. I used the skills from this course to secure my company's AWS infrastructure. Highly recommended for anyone serious about cybersecurity.

Rahul Menon Security Engineer, Bangalore

Machine Learning: Level-01

Machine Learning:Level-01

Overview

Learning Outcome

Syllabus

What You Will Learn

Regression & Classification

Ensemble Methods

Feature Engineering

Unsupervised Learning

What Our Students Say

Ready to Level Up YourCybersecurity Career?

Machine Learning:
Level-01

Ready to Level Up Your
Cybersecurity Career?