There is a GoLogica Machine Learning Master's program in Pune that will give you a deeper understanding of the ML algorithms and data modeling with AI tools. Through hands-on projects where you create and deploy real-time models of ML in real-world scenarios, you master the concepts of supervised and unsupervised learning, neural networks, and deep learning. Enroll today with GoLogica for a positive step in machine learning.
GoLogica Academic's Master Program features a structured curriculum, paving the way to Global scope.
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GoLogica having a 15+ years of experience on career transforming programs with industrial oriented Skills.
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GoLogica emphasizes practical learning with exercises, projects to equip you with real world application.
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Maximum Salary Hike
150%
Average Salary Hike
75%
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2000+
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Machine Learning Program Details
The Master's Program in Machine Learning by GoLogica in Pune trains professionals who have expertise for an active, gainful progressive stand in AI and machine learning fields. Therefore, in this program, all things will be there - from the more advanced knowledge of primary principles of machine learning to advanced topics like neural networks, deep learning, and data processing-and thus may be pretty suitable for beginners as well as experienced professionals.
This would open a wide perspective of the basic points of machine learning and focus on the differences of the three techniques involved: supervised, unsupervised, and reinforcement learning. It would review all algorithms, decision trees and its family, random forests, support vector machines, and various methods of clustering. Advanced topics, such as neural networks and deep learning, will be covered using tools like TensorFlow and Keras for more complex models.
You then apply those skills to practical projects so that you really do gain hands-on experience in solving practical problems. The projects that you will undertake will include subjects such as predictive modeling, image recognition, and natural language processing, so the work will qualify toward building up a portfolio of work to illustrate your skills to prospective employers.
In the master's course at GoLogica for Machine Learning, even though it focuses on technical skills, it still covers data handling, feature engineering, and model optimization. It teaches one to clean and preprocess their data very well so that it is in good accuracy and efficiency from the models. Its training further includes model evaluation and tuning techniques so you may really improve the performance of your machine learning models.
This course is ideal for Data Scientists, Software Engineers, and IT Professionals wishing to specialize in machine learning. Everything one needs to pursue a career path such as that of a Machine Learning Engineer, Data Scientist, or AI Specialist, including detailed training will be in store with this course by GoLogica.
You will be totally prepared at the end of this course with all knowledge and skills in building and deploying ML models. You will be an outstanding asset to any organization. Fast track your career by pursuing Master's Program in Machine Learning from GoLogica in Pune and be a master in the domain of AI and Machine Learning.
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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
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
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
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
Program Fee
Program Fee: 81000 /-
72900 /-
Discount: 8100
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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.
