Machine Learning using Python
- Offered bySimplilearn
- Private Institute
- Estd. 2010
Machine Learning using Python at Simplilearn Overview
Duration | 30 hours |
Start from | Start Now |
Total fee | ₹14,990 |
Mode of learning | Online |
Official Website | Go to Website |
Credential | Certificate |
Machine Learning using Python at Simplilearn Highlights
- Earn a certificate after completion of course from Simplilearn
- 30+ hours of blended learning
- Interactive learning with Google Colabs
- Lifetime access to self-paced learning content
Machine Learning using Python at Simplilearn Course details
Supervised and unsupervised learning
Linear and logistic regression
KMeans clustering
Decision tree
Boosting and Bagging techniques
Time series modeling
Kernel SVM
Naive Bayes
Random forest classifiers
Deep Learning fundamentals
This Machine Learning using Python course offers an in-depth overview of ML topics, including working with real-time data, developing supervised and unsupervised learning algorithms, regression, classification, and time series modeling
It is designed for students and professionals with a foundational understanding of programming and mathematics, the course explores a wide range of machine learning algorithms and practices
Machine Learning using Python at Simplilearn Curriculum
Lesson 01 Course Introduction
Course Introduction
Accessing Practice Lab
Lesson 02 Introduction to AI and Machine Learning
2.1 Learning Objectives
2.2 Emergence of Artificial Intelligence
2.3 Artificial Intelligence in Practice
2.4 Sci-Fi Movies with the Concept of AI
2.5 Recommender Systems
2.6 Relationship between Artificial Intelligence, Machine Learning, and Data Science: Part A
Lesson 03 Data Preprocessin
3.1 Learning Objective
3.2 Data Exploration Loading Files: Part A
3.2 Data Exploration Loading Files: Part B
3.3 Demo: Importing and Storing Data
Practice: Automobile Data Exploration - A
3.4 Data Exploration Techniques: Part A
3.5 Data Exploration Techniques: Part B
3.6 Seaborn
Lesson 04 Supervised Learning
4.1 Learning Objectives
4.2 Supervised Learning
4.3 Supervised Learning- Real-Life Scenario
4.4 Understanding the Algorithm
4.5 Supervised Learning Flow
4.6 Types of Supervised Learning: Part A
4.7 Types of Supervised Learning: Part B
4.8 Types of Classification Algorithms
4.9 Types of Regression Algorithms: Part A
4.10 Regression Use Case
4.11 Accuracy Metrics
Lesson 05 Feature Engineering
5.1 Learning Objective
5.2 Feature Selectio
5.3 Regressio
5.4 Factor Analysis
5.5 Factor Analysis Process
5.6 Principal Component Analysis (PCA)
5.7 First Principal Component
Lesson 06 Supervised Learning Classification
6.1 Learning Objectives
6.2 Overview of Classification
Classification: A Supervised Learning Algorithm
6.4 Use Cases of Classification
6.5 Classification Algorithms
6.6 Decision Tree Classifier
6.7 Decision Tree Examples
6.8 Decision Tree Formation
Machine Learning using Python at Simplilearn Placements
Particulars | Statistics (2024) |
---|---|
Average Salary | INR 14.00 Lakh |
Highest Salary | INR 16.00 Lakh |
Lowest Salary | INR 11.00 Lakh |