Machine Learning Training by Experts
Our Training Process

Machine Learning - Syllabus, Fees & Duration
Module 1 : CORE PYTHON
- Short history
- Introduction
- Features of Python
- Python2 Vs Python 3
- Python Installation
- Python Interpreter
- How to Run Python
- Basic Syntax
- Python Identifiers, Keywords and Indentation Rules
- Type Checking
- Input, Output, Variables, Data Type and Datatype Casting
Module 2 : MACHINE LEARNING
- Data Analysis
- Data Visualization
- Data Classification
- Supervised Learning Unsupervised Learning
Module 3 : SUPERVISED LEARNING
- Classification
- K-Nearest Neighbours
- Decision Tree
- Naive Bayes
- Logistic Regression
- Support Vector Machine
- Random Forest
- Logistic Regression
- Regression
- Single Linear Regression
- Multiple Linear Regression
Module 4 : UNSUPERVISED LEARNING
- Clustering
- Hierarchical Clustering
- KMeans Algorithm Association
Module 5 : DATA PREPROCESSING
- PCA
- Dimensionality reduction
- Correlation
- Features Extraction Algorithm
This syllabus is not final and can be customized as per needs/updates


Learning machine learning can help you advance your profession. By enrolling in NESTSOFT machine learning classes, you will gain exposure to industrial projects or machine learning certification from a specific area. Machine learning focuses on the development of computer algorithms that can access data and learn on their own. Can a machine, like a human, learn from skills or previous data? So here's where Machine Learning comes in. We live in a world surrounded by humans who can study everything using their abilities and learning abilities, as well as machines that follow our directions.
You'll also have the opportunity to work as a data scientist, Machine Learning engineer, or data engineer for several years and learn from industry specialists. The instructors are industry experts that work for top companies and have 10+ years of expertise in their industries. Machine learning is the most in-demand position in the information technology industry right now.
An overview of artificial intelligence and machine learning, fundamental principles for machine learning, data pre-processing, feature extraction, regression, logistic regression, nave Bayes, decision trees, kernel methods, and support vector machine and k-means and hierarchical clustering are among the topics covered in this course. Anyone who completes this course can expect a typical salary increase of 48% and be hired by one of our 100+ hiring employers.