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Machine Learning Master's Program in Delhi, IN

(4.6) 1480 ratings.

GoLogica offers a complete Machine Learning Master's Program in Delhi that will provide you with in-depth knowledge of algorithms, data processing, and model construction. Get practical knowledge with real-world projects to advance your career in this advanced profession.
Machine Learning Masters Program

Next Batch Starts

16th Nov 2024

Program Duration

12 Months

Learning Format

Online Bootcamp

Why Join this Program?

GoLogica Acadamic

GoLogica Academic's Master Program features a structured curriculum, paving the way to Global scope.

Industry Experience

GoLogica having a 15+ years of experience on career transforming programs with industrial oriented Skills.

Latest AI Trends

GoLogica Advanced Programs delivers cutting-edge AI Training, offering insights into the latest trends.

Hands-on Experience

GoLogica emphasizes practical learning with exercises, projects to equip you with real world application.

Learners Achievement

Maximum Salary Hike

150%

Average Salary Hike

75%

Haring Partners

2000+

Our Alumini

Machine Learning alumini

Machine Learning Program Details

Master in Machine Learning at GoLogica in Delhi is designed to propel professionals into the fast-paced world of data science and artificial intelligence. It will endow one with vast knowledge of the development, implementation, and deployment of machine learning models as machine learning progresses across different industries. Equip yourself with the tools to harness data-driven insights that transform business strategies.

 

A successful career in machine learning requires both theoretical and practical expertise. GoLogica Master's Program is developed based on insights from industry experts so that relevant skills and knowledge for real challenges in machine learning and data science are imparted to you.

 

Among topics to be covered in this curriculum will be supervised and unsupervised learning, neural networks, data processing, and model evaluation, among others. In every module, I will guide you through the intricacies of machine learning techniques and algorithms that drive innovations around various sectors.

 

Concepts involving complexity are learned only through the GoLogica Practical learning experience. This would include practical projects that simulate real-life machine learning scenarios in a training session for the application of learned knowledge and enhancement of problem-solving skills. This experiential learning best equips you to handle the actual machine learning projects with ease.

 

That means this dedicated support team is ready to assist you out with every issue and question related to the course so that learning is always seamless and productive.

 

Topics Covered in the Key Focus of the Program

 

  1. Introduction to Machine Learning: Familiarize yourself with basic concepts, algorithms, and tools used in machine learning
  2. Supervised and Unsupervised Learning: Understand concepts in classification, regression, clustering, and techniques of dimensionality reduction.
  3. Deep Learning and Neural Networks: How neural networks work and how to build deep learning models for complex data analysis.
  4. Data Preprocessing and Feature Engineering: Techniques on cleaning, preparing, and selecting the right features in your dataset to build more accurate models.
  5. Model Evaluation and Optimization: Discovery of model performance metrics and optimization techniques to improve the accuracy levels in your models.

 

After getting certified for the industry-approved credentials, such as AWS Certified Machine Learning—Specialty or even TensorFlow Developer Certification, by completing the Machine Learning Master's Program offered by GoLogica. These can instead lead to enhanced career prospects in the IT, finance, health care, and e-commerce sectors into more complex roles in machine learning.

 

Whether you look forward to climbing the corporate ladder or switching over to machine learning, the GoLogica Master's Program in Machine Learning prepares you by giving you the knowledge and the confidence to achieve your goals. That is why this program provides you with a comprehensive curriculum and hands-on experience on how to attain high-level success in the rapidly changing machine-learning landscape.

 

Become a successful machine learning practitioner like others who have successfully modified their entire careers at GoLogica with the help of our expert program. Take that first step to becoming an expert in machine learning today!

 

Join the GoLogica Master Course in Machine Learning in Delhi to be trained with the latest education, hands-on skills, and industry certification to groom you into a real machine-learning professional who can transform the standards of innovation and growth with never-ending opportunities. Sign up now and take it to the sky.

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
Python Training

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

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
Data Science with Python Training

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
Pyspark Certification Training

To become a master in Machine Learning?

Skills Covered

Machine Learning Masters Program skills covered

Tools Covered

Machine Learning Masters Program 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 Masters Program career support

Program Fee

Program Fee: 81000 /-

72900 /-

Discount: 8100

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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.

Machine Learning certificate

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.

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