Machine Learning Online Live Class by Experts
Our Training/Internship 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
- Since 2001, Making IT Experts by Experts
- Duration: 40 Hours (Vary as per your skill)
- Course Fees
- Individual Live Classes (1:1)
- Batch Classes @ Low Fees
- Training on Your Time, Any Where
- Access to Recorded Videos
- Practical Internship on Projects
- 100% Placement Support by our jobsHybrid.com
- Training/Internship Certificate
- Adelaide
- Albany
- Alice Springs
- Armidale
- Ballarat
- Bathrust
- Bendigo
- Brisbane
- Bunbury
- Busselton
- Cairns
- Canberra
- Central Coast
- Darwin
- Devonport
- Dubbo
- Geelong
- Geraldton
- Gold Coast
- Goulburn
- Hobart
- Launceston
- Lismore
- Melbourne
- Melton
- Mildura
- Newcastle
- Nowra
- Orange
- Perth
- Rockhampton
- Shepparton
- Sydney
- Tamworth
- Toowoomba
- Townsville
- Warrnambool
- Wollongong
Course Highlights
Our Locations
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. Machine learning is the most in-demand position in the information technology industry right now.
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. As a result of the increased demand, experts have been able to land the highest-paying positions. The Melbourne machine learning course covers the fundamentals of computational data processing, visualization, prediction, and current deep learning topics. 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. Anyone who completes this course can expect a typical salary increase of 48% and be hired by one of our 100+ hiring employers. Image recognition, speech recognition, traffic prediction, product recommendations, self-driving cars, and other applications of machine learning are just a few examples. The instructors are industry experts that work for top companies and have 10+ years of expertise in their industries. 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. 
