UpGrad Machine Learning Course

Upgrad Machine learning

Key Highlights of the Program

• Designed for Professionals in the Workplace
• 600+ Learning Hours
• There are over 15 case studies and assignments to choose from.
• 6 Capstone Projects that are both practical and hands-on
• Workshops on profile building and live coding
• IIIT Bangalore’s Executive PG Program & Alumni Status
• EMI options are available at no cost.
• 3 electives to personalize your study path Dedicated Student Success Mentor
• To improve the learners’ career persona, a portfolio website was created on Github.
• Sessions of Career Mentorship (1:1)
• Coaching for High Performance (1:1)
• Just-in-Time Interviews are a type of interview that takes place when it is most convenient
• Assessments of Industry Readiness
• Personalized Industry Session AI Powered Profile Builder Exclusive Job Opportunities Portal
• Bootcamp for Professional Development
• For non-academic questions, Student Support is accessible seven days a week, twenty-four hours a day, seven days a week. Please contact us at studentsupport@upgrad.com. Use the Learn platform’s “Talk to Us” option for urgent questions.

Machine learning, deep learning, computer vision, natural language processing, transformers, cloud, and MLOps are some of the most important topics you’ll learn.

Engineers, software and IT professionals, and data professionals are the target audience.

Job Prospects- MLOps Engineer, Data Engineer, Data Scientist, Machine Learning Engineer

Minimum Qualifications

Bachelor’s degree with a passing grade of 50% or above. A minimum of one year of technical job experience or a degree in mathematics or statistics with programming knowledge is required.

Syllabus

Experience 600+ hours of best-in-class information in the form of videos, case studies, and projects provided by premier instructors and industry professionals. 

3 Weeks of Pre-Program Preparatory Content

• Python for Data Science (Introduction to Python)
• SQL Data Analysis Data Visualization in Python (Optional)
• SQL Best Practices and Advanced SQL (Optional)
• Machine Learning Data Analysis in Excel Analytics Problem Solving Math

5 Weeks of Statistics and Exploratory Data Analytics

• Analyze exploratory data
• Introduction to Git and GitHub in the Cloud
• Statistical Inference
• Lending Club Case Study Hypothesis Testing

I7 Weeks of Machine Learning-1

• Regression with a Line
• Assignment for Linear Regression
• Logistic regression is a statistical technique for predicting the outcome of
• Model Selection with Naive Bayes

II – Machine Learning

• Seven Weeks
• Regression Analysis (Advanced)
• Assignment on Advanced Regression
• Machine to Support Vectors (Optional)
• Model Selection for Tree Models – Practical Considerations
• Clustering as a means of enhancing unsupervised learning
• Principal Component Analysis in Unsupervised Learning
• Case Study on Telecom Churn

8 Weeks of Deep Learning

• Neural Networks: An Overview
• Industry Applications of Convolutional Neural Networks
• Assignment on Convolutional Neural Networks
• Recurrent Neural Networks (RNNs) are a type of neural network that
• Gesture Recognition Neural Network Project

7 Weeks of Natural Language Processing

• Lexical Analysis
• Syntactical Analysis
• Assignment on Syntactic Processing
• Customer Complaint Ticket Classification Using Semantic Processing

10 Weeks Cloud Essentials: Intro to AWS ELective 1: DL with MLops

• Working with Amazon Web Services (AWS): a case study
• Introduction to MLOps
• MLS stands for “Data Lifecycle Operations.”
• Model Lifecycle Operations (MLOps)
• Assignment for MLops
• Advanced CV Advanced CV Advanced CV
• MLOps + Deployment: DL (Theory)
• MLOps + Deployment: DL (assignment)

Elective 2: Maps and NLP

• 10 Weeks of Cloud Essentials: AWS (Amazon Web Services)
• Working with Amazon Web Services (AWS): a case study
• Introduction to MLOps
• MLS stands for “Data Lifecycle Operations.”
• Model Lifecycle Operations (MLOps)
• Assignment for MLops
• Advanced Natural Language Processing (NLP) Advanced Natural Language Processing (NLP)
• Deployment + MLOps: NLP (Theory)
• Deployment + MLOps: NLP (assignment)

Elective 3: Artificial Intelligence Strategy

• ten weeks
• AWS Essentials: A Beginner’s Guide
• Working with Amazon Web Services (AWS): a case study
• Introduction to MLOps
• MLS stands for “Data Lifecycle Operations.”
• Model Lifecycle Operations (MLOps)
• Assignment for MLops
• Structured Problem Solving/ Data Storytelling, AI Strategy Framework
• Data architecture strategy and machine learning
• Putting AI Strategy into Practice
• The assignment is an AI approach.

Learning through Reinforcement (Optional)

Assignment on Classical Reinforcement Learning -Classical Reinforcement Learning Deep Reinforcement Learning Project

Projects in the Industry

• Real-world industry initiatives sponsored by prominent firms in a variety of areas provide opportunities to learn.
• Participate in real-world collaborative projects with student-expert interaction.
• Take advantage of learning from industry experts in person.
• Subjective feedback on your contributions that is tailored to you in order to help you develop.

Analysis of Telecom Churn

For a prominent telecom operator in India, solve the most critical business challenge.

Play Tic Tac Toe with an agent.

Learners will put their knowledge into practice. To teach an RL agent to play the game of name, Q-Learning was used.

Customer complaints are categorized.

Develop a solution to assist in determining the kind of complaint ticket.

Detection of Credit Card Fraud

Create a machine-learning model that can spot fraudulent transactions.

Advantages of Upgrading

Strong guidance and committed assistance to assist you in mastering Cyber Security.

Possibilities for advancement

• Elevate by upGrad: A virtual hiring drive that allows you to interview with upGrad’s 300+ hiring partners.
• Portal for Job Openings: At any one time, upGrad’s Job Opportunities page includes 100+ positions from upGrad’s hiring partners.
• To obtain an advantage in the application process, be the first to learn about job openings.
• Make contact with firms that are a good fit for you.

The Admissions Procedure

The first step is to take an online eligibility test.

The first step is to take an online eligibility test.

To check your aptitude, fill out an application and complete a brief 40-minute online exam with 18 questions.

Step 2: Review and Selection of Appropriate Candidates

All applications will be reviewed by our professors, who will take into account an applicant’s educational and professional experience, as well as any test scores. Following that, Offer Letters will be sent out, ensuring that you have a terrific peer group with whom to study and network.

Step 3: Register for Prep Content Access.

Make a simple block payment with the help of our financing partners if needed, get instant access to the prepped content, and get started on your upGrad adventure.

Frequently Asked Questions

Q. I’m not sure if this program is right for me.

If you are one of the following, this program is for you:

If you are acquainted with data wrangling, have implemented statistical or machine learning models in the past, or if you have any prior experience as a working professional, you should consider becoming a data scientist or senior data analyst. You should also have some R/Python/Scala experience.

If you have a formal education in statistics or mathematics, or if you have prior professional experience, you are a statistician.

If you have past expertise in constructing data pipelines/handling data warehouses and implementing ETL processes, you are a Data Engineer/Big Data Engineer. You should also be familiar with frameworks and technologies like as Hadoop and Spark.

Q. What can I anticipate from this program?

This curriculum is aimed at working professionals who want to learn advanced topics such as reinforcement learning, graphical models, natural language processing, and deep learning, as well as a solid foundation in statistics. Over the course of 13 months, this program requires constant work and time commitment.

Q. Is there any kind of certification available at the end of the program?

IIIT Bangalore will award an Executive PG Programme in Machine Learning and AI upon completion of the curriculum.

Q. What is the procedure for applying to this program?

UpGrad, IIITB, world-class instructors, and numerous industry professionals have put a lot of effort into conceptualizing and developing this program so that applicants may enjoy the finest learning experience possible. As a result, we want to make sure that all of the participants in this program have a strong dedication to Machine Learning and AI.

Applicants will be required to complete a 40-minute selection exam that will assess their mathematics and programming skills. If the following requirements are met, the candidates may be excluded from taking the test:

A Mathematical/Statistical Degree with a certain grade and more than 1 year of relevant analytical/programming experience

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