Machine Learning Program Details

Machine Learning (ML) is a branch of Artificial Intelligence (AI) that is involved with the making of computer programs that can modify when exposed to new data. This disruptive innovation has since evolved into an important element of many sectors, including health, finance, manufacturing, retail, and technology.

The Machine Learning Course Master’s Program at GoLogica is crafted systematically to help candidates gain extensive knowledge in the subject of machine learning along with the algorithms and tools. This program features complete course content in Python programming, data science, artificial intelligence, and statistics accompanied by projects to solve realistic problems. Designed as a set of engaging presentations and hands-on activities with tips from experienced practitioners, this program is intended to develop you into a machine learning model construction and deployment master.

This program is aimed at providing a comprehensive view of a set of concepts, methods, and software that are at the core of the ML area. It starts with supervised and unsupervised learning and goes on to concepts that are relatively recent arrivals on the data science horizon, like deep learning, reinforcement learning, neural networks, and so on.

The knowledge base of this course is configured in a way that will enable you to learn about both the theory and practical applications related to implementing machine learning models. On completion of the program, you will demonstrate the ability to select and apply appropriate machine learning frameworks and model-building techniques, data manipulation skills, and data-driven decision-making.

It is designed for those who are entering the field of machine learning as a career and for those who need to upgrade their knowledge within this rapidly developing subject area.

Key Highlights

Comprehensive Learning Path: The program covers topics such as Python programming, Data Science, Machine Learning algorithms, Artificial Intelligence, and PySpark.

Hands-on Projects: This course offers a lot of practical projects in different areas. These projects have certain real-world experiences with the usage of ML and AI tools and methods.

Expert Instructors: The program is tutored by professionals who understand what the program is all about and how best to impart it to the learners. It will assist learners in grasping the concepts of theories and applications of machine learning.

Industry-Relevant Curriculum: Due to the exigencies of course content developers, the curriculum is developed in consultation with professionals in the industry for learners to acquire the best tools and technologies being used in the machine learning field.

Career Support: By the end of the program, learners will be guided on how to find high-paying jobs in the machine learning industry and the facilitation of resume writing and interview preparation.

Flexible Learning: The program is fully self-paced with the option of live classroom teaching, and this allows the learner to choose between the two that best suit their lifestyle.

Top Skills You Will Learn

Machine Learning algorithms such as Supervised and Unsupervised algorithms
Data Science with Python
AI techniques, including Neural Networks and Deep Learning
Python Programming for data analysis and machine learning
PySpark for big data processing

Are you excited about this?

Machine Learning Syllabus

Python

Python was mainly developed for emphasis on code readability, and its syntax allows programmer to express concepts in fewer lines of code.Python is considered a scripting, language like Ruby or Perl and is often used for creating Web applications and dynamic Web content.

WEEK 3-4 20 Hours LIVE CLASS

History
Features
Setting up path
working with Python
Variable and Data Types
Operator

If
If- else
Nested if-else
For
While
Nested loops
Break
Continue
Pass

Accessing Strings
Basic Operations
String slices
Function and Methods

Accessing tuples
Operations
Working
Functions and Methods
Accessing list
Operations
Working with lists
Function and Methods

Defining a function
Calling a function
Types of functions
Function Arguments
Anonymous functions
Global and local variables
Importing module
Math module
Random module
Packages
Composition

Printing on screen
Reading data from keyboard
Opening and closing file
Reading and writing files
Functions
Exception
Exception handling
except clause
Try? Finally clause
User Defined Exceptions

Class and object
Attributes
Inheritance
Overloading
Overriding
Data hiding
Match function
Search function
Matching VS Searching
Modifiers
Patterns

Introduction
Architecture
CGI environment variable
GET and POST methods
Cookies
File upload
Connections
Executing queries
Transactions
Handling error

Socket
Socket Module
Methods
Client and server
Internet modules

Centers
Thread
Starting a thread
Threading module
Synchronizing threads
Multithreaded Priority Queue
Tkinter programming
Tkinter widgets

Artificial Intelligence (AI)

GoLogica is offering an instructor led extensive course on Artificial Intelligence(AI) course. Artificial Intelligence is also called as Machine intelligence. This domain is constantly evolving and many applications are slowly moving towards this platform .

WEEK 8-10 40 Hours LIVE CLASS

Artificial Intelligence Training.html

Introduction to Artificial Intelligence
Applications, Industries
and growth
Techniques used for AI
AI for everything
Different methods used for AI
Tradition Methods & New Methods
AI Agents

Introduction to Anaconda
Installation of Anaconda Python Distribution : For Windows
Mac OS
and Linux
Jupyter Notebook Installation
Jupyter Notebook Introduction
Variable Assignment
Basic Data Types: Integer
Float
String
None and Boolean; Typecasting
Creating
Accessing
and slicing tuples
Creating
accessing
and slicing lists
Creating
viewing
accessing
and modifying dicts
Creating and using operations on sets
Basic Operators: 'in', '+', '*', Functions
Control Flow

NumPy Overview
Properties
Purpose
and Types of ndarray
Class and Attributes of ndarray Object
Basic Operations: Concept and Examples
Accessing Array Elements: Indexing
Slicing
Iteration
Indexing with Boolean Arrays
Copy and Views
Universal Functions (ufunc)
Shape Manipulation
Broadcasting
Linear Algebra

Introduction to Pandas
Data Structures
Series
DataFrame
Missing Values
Data Operations
Data Standardization
Pandas File Read and Write Support
Data Acquisition (Import & Export)
Selection
Filtering
Combining and Merging Data Frames
Normalization method
Removing Duplicates & String Manipulation

Introduction to Data Visualization
Python Libraries
Plots
Matplotlib Features
Line Properties Plot with (x, y)
Controlling Line Patterns and Colors
Set Axis
Labels
and Legend Properties
Alpha and Annotation
Multiple Plots
Subplots
Seabo

Regression Problem Analysis
Mathematical modeling of Regression Model
Gradient Descent Algorithm
Programming Process Flow
Use cases
Programming Using python
Building simple Univariate Linear Regression Model
Multivariate Regression Model
Boston Housing Prizes Prediction
Cancer Detection Predictive Analysis
Best Fit Line and Linear Regression

Neurons
ANN & Working
Single Layer Perceptron Model
Multilayer Neural Network
Feed Forward Neural Network
Cost Function Formation
Applying Gradient Descent Algorithm
Backpropagation Algorithm & Mathematical Modelling
Programming Flow for backpropagation algorithm
Use Cases of ANN
Programming SLNN using Python
Programming MLNN using Python
Digit Recognition using MLNN
XOR Logic using MLNN & Backpropagation
Diabetes Data Predictive Analysis using ANN

Hierarchical Clustering
K Means Clustering
Use Cases for K Means Clustering
Programming for K Means using Python
Image Color Quantization using K Means Clustering Technique
Clustering

Dimensionality Reduction
Data Compression
Concept and Mathematical modeling
Use Cases
Programming using Python
IRIS Data Analysis using PCA

Understand limitations of A Single Perceptron
Understand Neural Networks in Detail
Backpropagation : Learning Algorithm
Understand Backpropagation : Using Neural Network Example

Why Deep Learning?
SONAR Dataset Classification
What is Deep Learning?
Feature Extraction
Working of a Deep Network
Training using Backpropagation
Variants of Gradient Descent
Types of Deep Networks

Introduction to CNNs
CNNs Application
Architecture of a CNN
Convolution and Pooling layers in a CNN
Understanding and Visualizing a CNN
Transfer Learning and Fine-tuning Convolutional Neural Networks
Image classification using Keras deep learning library

Data Science with Python

GoLogica provides Data Science with Python Training This course has been designed with a focus on quality and simplicity making it ideal for Beginners or for those looking for a refresher on Data Science with Python. It gives an engaging learning experience covering everything you need to know about Data Science.

WEEK 4-7 30 Hours LIVE CLASS

Your first program
Types
Expressions and Variables
String Operations

Lists and Tuples
Sets
Dictionaries

Conditions and Branching
Loops
Functions
Objects and Classes

Reading files with open
Writing files with open
Loading data with Pandas
Working with and Saving data with Pandas

ChatGpt

In this course, you will learn about the workings of OpenAI’s ChatGPT model, the model architecture, and the fine-tuning techniques. You will also discover in detail how to embed ChatGPT into various applications, control conversation flows, and fine-tune it for distinct tasks. Applied, you’ll learn about the operative utilization and development of AI chatbots as well as NLP, making ChatGPT your robust tool in AI capability.

24 Hrs 24 Hrs Online

ChatGpt Complete Course: Beginers to Advanced

Python Statistics for Data Science

The GoLogica Python Statistics course offers students to learn what it takes to be a data scientist and the basic statistical methods required. In this course, you will find out about descriptive statistics, probability, inferential statistics, and hypothesis testing. The course involves the use of libraries such as NumPy, Pandas, and SciPy, prevalent techniques in Python for analyzing real data together with statistical methods. By the end, you’ll be able to make sense of your data and build data models using one of the preferred languages for anyone working in data science or machine learning toda —Python.

35 hours 35 Hours Online

Python Statistics for Data Science Course

Pyspark

This course provides guidelines on how to process big data through PySpark, which is a vital instrument in big data processing and compute clusters. You will learn how to manipulate big data using Spark’s data structures, including RDDs and Spark Dataframes. The course also introduces Machine Learning with PySpark to help you build scalable ML models. This certification makes you ready to work on big data technologies professionally.

35 Hrs 35 Hrs Online

To become a master in Machine Learning?

Skills Covered

Tools Covered

Career Support

Personalized Industry Session

This will help you to better understand the Machine learning.

High-Performance Coaching

you will be able to grow your career by broadening your proficiency in Machine learning.

Career Mentorship Sessions

With this, the students will be able to decide their careers in the right way.

Interview Preparation

We Help with face-to-face interaction through mock interviews & Exams

Machine Learning Master’s Program career support

Program Fee

Program Fee: 81000 /-

72900 /-

Discount: 8100

Paypal

Debit/Credit

UPI

Machine Learning Certification

GoLogica Machine Learning Certification holds accreditation from major global companies worldwide. Upon completion of both theoretical and practical sessions, we offer certification to both freshers and corporate trainees. Our certification on Machine Learning is recognized globally through GoLogica, significantly enhances the value of your resume, opening doors to prominent job positions within leading MNCs. Attainment of this certification is contingent upon the successful completion of our training program and practical projects.

Job Outlook

Personalized Industry Session

The U.S. Bureau of Labor Statistics (BLS) forecasts a 22% increase in employment for Machine Learning from 2021 to 2031, significantly outpacing the average for all occupations. Additionally, Machine Learning Ventures predicts 3.5 million unfilled cybersecurity jobs worldwide by 2025.

High-Performance Coaching

According to the BLS, Machine Learning professionals are well-compensated. The median annual wage for Data Engineer was $110,000 and $160,000 PA It’s depending on factors such as experience, location, and specific job responsibilities.

Job Titles

Are you preparing for a interview? If yes, our expert tutors will help you with this.

Machine Learning Engineer
AI Engineer
Data Scientist
ML/AI Research Analyst
ML/AI Consultant
Business Intelligence Analyst

Machine Learning Faq’s

The Machine Learning Master’s Program is a course that consists of all the necessary topics, starting from the basic understanding of machine learning, data science, and AI up to the most complex concepts. The material includes concepts including supervised and unsupervised learning, reinforcement engineering, projects, and real-life use cases.

The program is built for working professionals looking forward to becoming a Machine Learning Engineer, Data Scientist, AI Engineer, or Data Analyst. It is also appropriate for Software engineers, IT personnel, or recent employees desiring to make a career change to be an ML engineer.

The program has several modules that address different areas of Machine Learning, e.g. data preprocessing, model construction, distribution, deeper learning, as well as AI applications. The program also includes real-life projects and a final project.

The course generally takes between 6 and 12 months, depending on your speed and commitment and the several hours you spend per week.

The program is fully online, and live instructor-led courses are delivered as well.

Yes, Python is the principal language used for implementing machine learning algorithms and models.

Some of the positions are AI Engineer, Machine Learning Engineer, ML/AI Consultant, Data Scientist, and Business Intelligence Analyst.

Machine Learning experience is not necessary, though knowledge of Python and statistics is desirable.

The average salary for ML specialists is between 10 lakhs and 12 lakhs annually.

This program provides many-sided learning with lessons and presentations by professionals, practical work, individual consultations, and training in demanded skills.

Career support includes 1:1 mentorship, interview preparation, resume creation, and job suggestion services.

Learners have access to 24/7 support for technical queries, mentorship from ML professionals, and guidance on projects and assignments.

Yes, there are coding-related quizzes as well as coding assignments that are done throughout the program.

Highlights of the program include programming with Python, Big Data with Apache PySpark, Data Science, ChatGPT, and more industry-related technologies.

Yes, the mode of operation can be either part-time or full-time, depending on the user’s schedule.

Yes, you will have lifetime access to all recorded sessions and course materials after the completion of the program.

It is possible to register directly from GoLogica’s website by choosing the Machine Learning Master’s Program and filling out the registration application form.

The tutorials are in the form of assignments and projects, which are graded by the instructors, and you receive feedback for improvement.

International students are welcome to the program, and all lessons are delivered online.

While in live classes, if you did not attend or were unable to attend certain classes, you can be able to view the recorded session at your own time.

Yes, the program includes personalized 1:1 professional sessions with mentors in the industry.

Yes, there is. You will be awarded a Machine Learning Master’s Program certification if you clear the course and the capstone project.

It gives you enough knowledge about how you can build the models and algorithms and implement the solution. They offer practical exercises and a final project that lets you show the skills you have learned to prospective employers.

Yes, you will receive support from tutors and instructors throughout your process of completing the capstone, and they will gladly assist you if you encounter any problems on the way.

Particular classes may allow the students to work in groups on certain assignments; other classes may prefer individual work.

PySpark refers to the use of the Spark programming interface in Python, where you can complete the analysis of large data and create, train, and use machine learning models.

Yes, this course can accommodate beginners who have a desire to learn machine learning and weak programming skills. The concepts in the course are introduced at the basic level and gradually build up to expert levels.

Yes, the program has a flexible schedule; for instance, the classes may be conducted on weekends for working learners.

Yes, the program is designed for working individuals, flexibility in the hours of learning, and the need for part-time learning.

This course gives you the basic and advanced skills required in data science as far as data analysis and building models are concerned to ensure that you make a transition to data science positions.

Machine Learning Master’s Program

16th Oct 2024

12 Months

Online Bootcamp

Why Join this Program?

GoLogica Acadamic

Industry Experience

Latest AI Trends

Hands-on Experience

Learners Achievement

Maximum Salary Hike

150%

Average Salary Hike

75%

Haring Partners

2000+

Our Alumini

Machine Learning Program Details

Are you excited about this? Get in Touch

Machine Learning Syllabus

Python

WEEK 3-4 20 Hours LIVE CLASS

Course Content

Introduction and basic Syntax

Conditional & Control Statements and Looping

String Manipulation

Dictionaries

Functions and Modules

Input-Output and Exception Handling

OOPs concepts and Regular expressions

CGI and Database

Networking

Multithreading and GUI Programming

Artificial Intelligence (AI)

WEEK 8-10 40 Hours LIVE CLASS

Course Content

Artificial Intelligence Training

Introduction to Artificial Intelligence

Python: Environment Setup and Essentials

Mathematical Computing with Python (NumPy)

Data Manipulation with Python (Pandas)

Data Visualization in Python using Matplotlib

Linear Regression

Artificial Neural Networks

Principle Component Analysis

Deep Dive into Neural Networks

Master Deep Networks

Convolutional Neural Networks (CNN)

Data Science with Python

WEEK 4-7 30 Hours LIVE CLASS

Course Content

Python Basics

Python Data Structures

Python Programming Fundamentals

Working with Data in Python

ChatGpt

24 Hrs 24 Hrs Online

Course Content

Python Statistics for Data Science

35 hours 35 Hours Online

Course Content

Pyspark

35 Hrs 35 Hrs Online

Course Content

To become a master in Machine Learning? Enroll Now

Skills Covered

Tools Covered

Career Support

Personalized Industry Session

High-Performance Coaching

Career Mentorship Sessions

Interview Preparation

Program Fee

Program Fee: 81000 /-

72900 /-

Machine Learning Certification

Job Outlook

Personalized Industry Session

High-Performance Coaching

Job Titles

Are you excited about this?

To become a master in Machine Learning?