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

Candidates will acquire the fundamental concepts and intuition underpinning modern machine learning algorithms, as well as a more formal knowledge of how, when, and why they work, in this course.
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. Image recognition, speech recognition, traffic prediction, product recommendations, self-driving cars, and other applications of machine learning are just a few examples. Can a machine, like a human, learn from skills or previous data? So here's where Machine Learning comes in.
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. You'll need data training capabilities, algorithm basics, advanced, automation, and iterative processes, ensemble modeling, and scalability to build a strong ML (machine learning) system.
Machine Learning Engineer, Data Architect, Data Manager, Machine Learning Specialist, and more job profiles are available to machine learning certification holders.
. As a result of the increased demand, experts have been able to land the highest-paying positions. By enrolling in NESTSOFT machine learning classes, you will gain exposure to industrial projects or machine learning certification from a specific area.