Interested in this College?
Get updates on Eligibility, Admission, Placements Fees Structure

Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery	Frequency Of Classes
English	Self Study, Virtual Classroom	Video and Text Based	Weekends

Course Overview

Machine Learning serves as one of the biggest applications of data in today’s digital world. The Post Graduate Program in Machine Learning certification course is specifically designed for working professionals to train them with relevant skills. This 12-months program provides candidates with exhaustive hands-on training to develop the unique and necessary set of skills required for a successful career in a rapidly growing field. Candidates not only understand the best concept and algorithms of machine learning but also know how to apply them.

The course is perfectly designed to offer comprehensive skills to learners so that they can work as data science professionals. Various machine learning concepts and algorithms including supervised and unsupervised learning, PG Program in Machine Learning training. enables candidates to prepare for a better career path. If an employed professional has the required qualifications plus a robust desire to enhance their career in the highly rewarding domain of machine learning, then this program is ideal.

Also Read: Great Learning Certifications

The Highlights

Post Graduate Level Certification course
Duration is 7 months
Get a comprehensive curriculum
100% online course
Certificate from Great Lakes Executive Learning

Programme Offerings

Classroom sessions
Online Format
Lab Sessions
Capstone Project
assignments
Career Assistance
20+ Hands on Exercises

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	University of Texas, AustinGreat Learning

The fee for PG Program is GST inclusive and includes all the applicable charges. PG Program in Machine Learning certification fee is Rs. 1,25,000 + GST.

Eligibility Criteria

Educational Qualification

Bachelor’s Degree: Candidates must possess a Bachelor’s degree with at least 50% of aggregate marks or equivalent grade. The degree can be either in computer science, mathematics, engineering, or electronics.
Familiar with programming: Candidates must be comfortable with the use of a programming language like Python to applying for the Post Graduate Program in machine learning. Apart from it, learners must know college-level statistics and mathematics.

Working Experience

A minimum of 2 years of experience is efficient to learn the concepts and algorithms of machine learning. Though not necessary, still many institutions prefer that candidates applying for this program have some experience in working.

Certification Qualifying Details

After the hands on exercises, and exams get over students shall be receiving the PGP- Machine Learning certification by Great Lakes Executive Learning.

What you will learn

Machine learningConceptual Understanding

After the PGP- Machine Learning certification syllabus is completed, the candidate's A rich plus flexible learning methodology enables candidates to pursue the ML program without any break. Machine Learning includes a set of various algorithms that participants can learn from and respond to large data sets rapidly. Apart from learning and enhancing their skills, candidates can get exposure and academic ability to show their passion. They can learn:

Gain deep conceptual understanding: Post Graduate Program in Machine Learning program helps learners to gain perfect understanding and skills that are highly appreciated by the industry. It instructs participants on how to find patterns in data and learn to code. A professional certification program provides a great way for candidates looking to accomplish certain career goals in a short time.
Machine Learning Algorithms: There are various algorithms in machine learning that operate at expedited levels. Candidates get the ability to identify, process, and create efficient data based on customer leads, revenue rates, and other processes. Learners get practical learning on ML concepts and techniques, mathematical aspects, hands-on modeling, and many more.
Applying ML Algorithms to practical applications: Learning how to apply machine learning concepts and algorithms to practical applications is crucial. Participants get a chance to acknowledge the impact of ML in real-life situations on customer loss or attainment.

Who it is for

Machine Learning EngineerData Engineer

Engineering graduates: Candidates holding a Bachelor’s degree in computer science and having a keen interest in learning ML algorithms can apply for this course, and become data engineers or ML engineers.
Having programming experience: Learners who are not from a computer science background, but have efficient knowledge and programming experience can apply for PGP- Machine Learning course.
Working Professionals: Employed professionals who have high knowledge of programming languages like C++, Python, or data structures can apply. Anyone with a statistics/ engineering/ analytics background is eligible to apply for this course.

Admission Details

Candidates should consider significant steps to fill out the admission form for the PG Programme in Machine Learning classes.

Application Form: All the learners interested in applying for PGP in machine learning should fill out the form. The application forms for the program are available online.
Admission Test: The admission panel will check the application forms and then shortlist candidates. Participants shortlisted have to pass an interview.
Offer Letter: Those candidates who clear the interview will receive an offer letter from the admission director’s office. If candidates are highly interested, then they can accept the offer letter and pay a fee.

Application Details

Candidates have to mention their personal as well as professional details in PGP- Machine Learning application form.

Personal Details: Name of the applicant, mobile number, email address, and current city.
Professional Details: Working experience, programming background (like Python, C, R), and years of experience.

The Syllabus

Python for AI and ML

Python Basics
Jupyter notebook- Installation and Function
Python functions, packages and routines
Pandas, NumPy, Matplotlib, Seaborn
Working with arrays, data structures, data frames, and vector

Applied Statistics

Descriptive Statistics
Inferential Statistics
Probability and Conditional Probability
Probability Distributions - Types of distribution – Binomial, Poisson & Normal distribution
Hypothesis Testing

Supervised Learning

Multiple Variable Linear Regression
Multiple Regression
Logistic regression
K-NN Classification
Naïve Bayes Classifiers
Support Vector Machines (SVM)

Unsupervised Learning

K-means Clustering
Hierarchical Clustering
High-dimensional Clustering
Dimension Reduction- PCA

Ensemble Techniques

Decision Trees
Random Forests
Bagging
Boosting

Featurization, Model Selection, and Tuning

Feature Engineering
Model Selection and Tuning
Model Performance Measures
Regularising Linear Models
ML Pipeline
Bootstrap sampling
Grid search CV
Randomized search CV
K fold cross-validation

Recommendation Systems

Introduction to Recommendation Systems
Content based Recommendation System
Popularity Based Model
Collaborative filtering(User similarity & Item similarity)
Hybrid Models

EDA

"Pandas-Profiling" Library

Time Series Forecasting

ARIMA Approach

Model Deployment

Kubernetes

Evaluation process

There are several mock interviews, and workshops organised to make sure that all participants are competent and capable to learn different machine learning algorithms. To ensure that participants are understanding and receiving the best possible experience of learning, various institutions conduct PGP- Machine Learning exam. Quizzes are also directed during the program. For some subjects like Foundation block for Python, two quizzes are conducted, for supervised learning, four quizzes are conducted, for recommendation systems, there are three quizzes, and so on.

Instructors

University of Texas, Austin Frequently Asked Questions (FAQ's)

1: What is a PG Program in Machine Learning?

PGP- Machine Learning is a 7-month certification program that covers numerous machine learning algorithms. The course is specifically designed to help candidates gain practical knowledge and accelerate entry into machine learning roles.

2: Who can pursue a PG Program in Machine Learning?

Employed professionals holding a Bachelor’s degree in B.E or B.Tech, and having working experience in technology-related roles can pursue this course. Additionally, Bachelor's degree holders in any stream having an interest in learning programming and ML algorithms can apply for PGP in Machine Learning.

3: What type of learning experience can I expect while pursuing PG Program in Machine Learning online course?

The content delivered by professional experts and world-renowned faculty will be largely asynchronous. Apart from the regular classroom sessions, candidates will have live lectures and lab sessions dedicated to solving all the programming queries and doubts.

4: I am not from a data science background. Can I apply for PG Program in Machine Learning?

Any candidate not holding a degree in engineering, statistics, computer science, or statistics cannot apply for PGP- Machine Learning certification program. In addition to it, participants must be familiar with some fundamental programming tools and frameworks.

5: What can learners expect after completing the PG Program in Machine Learning?

Post Graduate Program in Machine Learning is beneficial for professionals looking to pick up skills in advanced ML concepts. After completing the course, candidates can become capable of applying graphical models, reinforcement learning, and other ML algorithms in real-life applications.

6: What is the scope after getting PG Program in Machine Learning certification?

The program helps candidates learn the fundamentals of machine learning and thus take their careers to the next level. Participants can apply for a data engineer, machine learning scientist, machine learning engineer, or any other role.

7: How is the PG Program in Machine Learning different from Masters in ML?

Lower cost is one of the major differences why candidates choose PGP- Machine Learning as compared to the Master’s program. Additionally, students get unlimited 1:1 mentorship support from professional experts.