Advanced Machine Learning Engineering

Online Live | 40 Hours | Basic Certification
19,900.00 +GST

Classes starts from 31st March 2024

Faculty would be from the industry

To further the objectives of EICT Academy under the Ministry of Electronics & Information Technology (MeitY), E&ICT Academy, IIT Kanpur brings you various courses in Emerging Technologies, Computer Sciences, Entrepreneurship, Business and many more. This course is curated and delivered by Industry Experts equipped with a wealth of experience and an in-depth understanding of the subject matter.


  • Start Date : 31st March 2024
  • Course Type: Comprehensive 40-hour program
  • Duration : 2 Months
  • Total Lectures: 20
  • Skill Level: Intermediate
  • Assessments: Assignments, Final Assessment
  • Certificate: Yes 

For Self-Paced Programs: 2 Doubt Session(s)/Master Classes 

Objective / Outcome Expected

  • Gain proficiency in machine learning engineering principles and application.
  • Develop expertise in supervised and unsupervised learning algorithms.
  • Master model evaluation, selection, feature engineering, and scalability.
  • Hands-on experience in developing and deploying machine learning models.

Target Audience

  • Ideal for anyone who wishes to learn the fundamentals of machine learning engineering and pursue a career in this rapidly growing field.
  • Suitable for individuals with a background in programming, database management, or data analytics.
  • Also beneficial for CXO-level and middle management professionals looking to enhance their analytics capabilities. 

Key Features

  • Comprehensive coverage of advanced machine learning engineering topics.
  • Hands-on experience through practical projects.
  • Certification upon successful completion. 

Faculty Members

  • S. Aggarwal
  • Nandan Mishra
  • Niraj T.
  • Shantam D.
  • U. Tiwari
  • S. Garg

Delivery Mode & Duration

Online Live Mode- 2 Months (40 Hours Online Live sessions + 60 Hours of Assignment and Hands on)


Module 1: Supervised and Unsupervised Learning Algorithms (10 hours)

  • Introduction to supervised and unsupervised learning
  • Decision trees and ensemble methods
  • Support Vector Machines (SVM)
  • Clustering algorithms (e.g., K-means, DBSCAN)
  • Dimensionality reduction techniques (e.g., PCA, t-SNE) 


Module 2: Model Evaluation and Selection (10 hours)

  • Evaluation metrics for classification and regression models
  • Cross-validation and model validation techniques
  • Bias-Variance trade-off and overfitting
  • Hyperparameter tuning and model selection
  • Assembling and stacking methods 


Module 3: Feature Engineering and Selection (10 hours)

  • Feature extraction and transformation techniques
  • Handling missing values and outliers
  • Feature scaling and normalization
  • Dimensionality reduction methods
  • Feature selection algorithms (e.g., Lasso, Recursive Feature Elimination)


Module 4: Model Deployment and Scalability (10 hours)

  • Model deployment strategies and considerations
  • Containerization and cloud deployment platforms
  • Scalable model architectures (e.g., distributed computing, GPU acceleration)
  • Model monitoring and performance optimization
  • Continuous integration and deployment (CI/CD) pipelines 


Section 1: Advanced Machine Learning Engineering Course Curriculum

Question 1: What is the Advanced Machine Learning Engineering Course?

Answer 1: The Advanced Machine Learning Engineering Course is an in-depth and comprehensive program designed to equip participants with advanced knowledge and skills in machine learning engineering. It covers supervised and unsupervised learning, model evaluation, feature engineering, and model deployment, offering a deep dive into this field.

 Question 2: What should I expect from the Data Analyst (40 hours) Course?

Answer 2: Expect to acquire a deep understanding of data analysis fundamentals. This course covers key topics, including exploratory data analysis, data visualization, statistical analysis, hypothesis testing, SQL, and business intelligence tools. Practical projects and hands-on experience are integral components of the program.

Question 3: What should I NOT expect from the Advanced Machine Learning (40 hours) Course?

Answer 3: This course is designed for individuals at a beginner skill level in data science. It is an advanced machine learning course. If you are an advanced data scientist, you may find this course less suitable for your needs.

Question 4: What topics/modules are covered in the Advanced Machine Learning Engineering Course?

Answer 4: This course is divided into several modules, including supervised and unsupervised learning algorithms, model evaluation and selection, feature engineering and selection, and model deployment and scalability. Each module provides a strong foundation in machine learning engineering.

Question 5: What type of learning experience should I expect from this course?

Answer 5: This course offers 100% LIVE Online delivery for doubt sessions and master classes. The learning experience is interactive and enriched by lectures from experienced instructors. Real-time interaction and question resolution are integral to the course.

Question 6: Is a certification granted upon completing the Advanced Machine Learning Course?

Answer 6: Yes, upon successful completion of the program, you will receive a certification from the prestigious IIT Kanpur. This certification is recognized in the industry and is secured using blockchain technology.

Question 7: When does the course start, and how long does it take to complete?

Answer 7: The course’s duration and start date may vary based on the specific program you choose. For precise information on course schedules, we recommend referring to the official website.


Section 2: Training Pedagogy for Advanced Machine Learning Engineering Course

Question 1: How will the course be delivered?

Answer 1: The complete course will be delivered 100% ONLINE LIVE through dependable online meeting tools. Only class recordings will be shared with you for revision or when you miss any class.

Question 2: What happens if I miss a doubt session or live class?

Answer 2: We understand that life can get a bit busy sometimes. If you miss a class due to urgent and unavoidable circumstances, we shall assist you with the recordings which will be available on the portal, you have enrolled for a program for your career enhancement, and our sincere advice would be to absent yourself from the class only in extreme, urgent, and unavoidable circumstances. It’s just a matter of few months when this course will be finished, and you embark on a bright career.

Question 3: How many assignments and projects are included in the course?

Answer 3: Each module will have 2 assignments. After completion of each module, there will be a minor project. By the completion of the training, every participant should undergo one month of capstone. Throughout the course, you’ll have a series of hands-on assignments that reinforce the concepts you learn. These assignments are designed to help you apply your knowledge practically and build a strong foundation in full stack development.

Question 4: Who will be there to assist me if I have a doubt?

Answer 4: As it is a 100% ONLINE LIVE training with two-way communication, you can get your doubts resolved then and there.

Before the start of every class, the faculty will be available for 10 to 15 minutes to clear your doubts.

Apart from this, we have weekly two-hour doubt sessions, where you can ask doubts one-to-one. We foster a supportive learning environment. Our experienced instructors and dedicated support team are available to address any doubts or questions you may have during the course. You can reach out through our communication channels for timely assistance.

Question 5: What do I need for the training?

Answer 5: To make the most of the training, you’ll need a computer or laptop with a stable internet connection. You’ll also need code editing software, which we will guide you on setting up. A curious mind and enthusiasm to learn are the key ingredients for success!

Question 6: What are the prerequisites for this course?

Answer 6: This course is designed for individuals at an intermediate skill level in machine learning engineering. It’s essential to have a foundational understanding of machine learning concepts and some experience with programming.

Question 7: Will we get value add sessions?

Answer 7: Absolutely, we believe in providing holistic learning. Apart from the core curriculum, there will be master trainers and industry experts who will deliver value-added sessions, workshops, and seminars to enhance your soft skills, communication abilities, and industry insights.

Question 8. Who all will be our instructors?

Answer 8: Our instructors are experienced industry professionals with a deep understanding of full stack web development. They bring practical insights and real-world examples to the classroom, ensuring an engaging and valuable learning experience.


Section 3: Time Commitment for Advanced Machine Learning Engineering Course

Question 1: What is the time commitment expected for the program?

Answer 1: To successfully graduate from the Advanced Machine Learning Course, we recommend dedicating at least 12-15 hours per week. This commitment ensures that you can effectively engage with the course material, complete assignments, and gain a comprehensive understanding of the concepts. While the curriculum is robust, we have designed the course with the needs of working professionals in mind, making it manageable and accommodating.

Question 2: Will the course require different time commitments for different modules or topics?

Answer 2: While the time commitment may vary slightly based on the complexity of the modules, it’s advisable to maintain a consistent amount of study time each week to stay on track and ensure you grasp all the concepts.


Section 4: Career Prospects and Support for Advanced Machine Learning Engineering Career

Question 1: What are the career prospects after completing the Advanced Machine Learning Engineering Course?

Answer 1: Completing the Advanced Machine Learning Engineering Course opens up various career opportunities in the field of machine learning engineering. Graduates may qualify for positions that require advanced knowledge in supervised and unsupervised learning, model evaluation, and model deployment, including roles in industries where machine learning applications are essential.

Question 2: How will my doubts/questions be addressed in an online program?

Answer 2: In the Course, you have access to a dedicated peer-to-peer discussion forum. Here, you can post your queries, and your peers, faculty members, and teaching assistants will provide answers within a day. Regular Q&A sessions with faculty members are conducted to clarify any conceptual doubts. This dynamic learning environment ensures that your questions are addressed promptly and comprehensively.

 Question 3: Will I receive special career services or support during the course?

Answer 3: As you embark on your Data Analyst journey, you can trust that the course is designed to provide holistic support, ensure effective doubt resolution, and equip you with the resources needed for a successful career in the field of data analytics.


Section 5: Course Fees, Refund Policy, and Financials

 Question 1: What is the fee for the program?

Answer 1: The fee for the Data Analyst Course is INR 19,900 excluding GST plus applicable taxes.

Question 2: How can I make payments for the program?

Answer 2: All training fees must be paid to the designated IFACET – IITK account. Payments should not be made to any other entity or individual.

Question 3: Can I pay program fees in EMIs? If not, can you assist me in securing one?

Answer 3: Yes, you have the option to convert the program fees into a no-cost EMI (Equated Monthly Installment) plan with your credit card. This allows you to pay in convenient installments.

Question 4: Will I have to pay any extra amount for EMI transactions?

Answer 4: Choosing the 0% credit card EMI option typically means that processing fees or down payments are not charged. However, please note that your bank may apply GST or other taxes on the interest component of the EMI. You should check with your bank for specific details.

Question 5: What is the Refund Policy of the program?

  Answer 5: Refund Policy:

Before the Start of the program

  • Refunds can be claimed for the paid amount towards the Program before the Program Start Date. This can be done by getting in touch with your academic counsellor.
  • Refund requests can also be initiated by reaching out to your Admissions Counsellor via email, providing reasons for withdrawal. A processing fee of 5% of the program will be deducted from the total amount paid.
  • It takes 3 to 4 weeks to refund the fees to your account from the date of acceptance of your refund request. The fees shall be refunded in the same account from which it was paid to us.
  • No refund requests will be entertained under any circumstances if raised after the Cohort Commencement Date.

After the commencement of the program:

  • The candidate is eligible for 90% refund of the program fees if he wishes to withdraw from the program within 15 days of the start of the program.
  • Such requests for refund shall be intimated to us over an email. There should always be a confirmation from our end that we have received your request.
  • It takes 3 to 4 weeks to refund the fees to your account from the date of acceptance of your refund request. The fees shall be refunded in the same account from which it was paid to us.
  • No refund requests will be entertained under any circumstances if raised after 15 days of the start date of the program.


Sample Certificate