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Diploma in Industrial Machine Learning Management

Rs.7,000 Rs.3,500

IISDT Offers 50% discount on all courses. Enroll your course today to avail discount offer. Government Job Valid Diploma/Certificate.

Machine learning is a process that needs inputs from many devices to feed data to it so that data can be collected. evaluated, and used to develop knowledge about how a production line produces the products and parts it does.


Course Name: Diploma in Industrial Machine Learning Management

Course Id: DIMLM/Q1001.
Education Qualification:12th Pass.

Duration: 370 Hrs (Equivalent to One Year).

Total Credits: 18.

How You will Get Diploma Certificate:

Step 1- Select your Course for Certification.

Step 2- Click on Enroll Now.

Step 3- Proceed to Enroll Now.

Step 4- Fill Your Billing Details and Proceed to Pay.

Step 5- You Will be Redirected to Payment Gateway, Pay Course and Exam Fee by Following Options.

Card(Debit/Credit), Wallet, Paytm, Net banking, UPI and Google pay.

Step 6- After Payment You will get Study Material Login id and Password on your email id.

Step 7- After Completion of  Course Study give Online Examination.

Step 8- After Online Examination you will get Diploma Certificate soft copy(Scan Copy) and Hard Copy(Original With Seal and Sign).

Step 9- After Certification you will receive Prospect Job Opportunities as per your Interest Area.

Online Examination Detail:

  • Duration- 120 minutes.
  • No. of Questions- 60. (Multiple Choice Questions).
  • 10 Questions from each module, each carry 10 marks.
  • Maximum Marks- 600, Passing Marks- 40%.
  • There is no negative marking in this module.
How Students will be Graded:
191-100O (Outstanding)
281-90A+ (Excellent)
371-80A (Very Good)
461-70B (Good)
551-60C (Average)
641-50P (Pass)
70-40F (Fail)

Benefits of Certification:

  • Government Authorized Assessment Agency Certification.
  • Certificate Valid for Lifetime.
  • Lifetime Verification of Certificate.
  • Free Job Assistance as per your Interest Area.


Introduction to Machine Learning: Sample application, robotics, social network, autonomous car sensors, autonomous car technology, learning of object parts, training on multiple objects, scene labeling via deep learning, inference from deep learned models, machine learning in automatic speech recognition, impact of deep  learning in speech technology, types of  learning.

Machine Learning Techniques and Algorithms: Introduction to machine learning, important elements in machine learning, principal component analysis, linear Regression, logistic regression, stochastic gradient descent algorithms, creating a machine learning architecture, hierarchical clustering, types of learning algorithm.

Data Science Tool kit: Introduction to data sciences, using data science to extract meaning from data, usage of data science tools environment, data manipulation using pandas, data visualization matplotlib, techniques using python tools, applying data  science in industry.

Machine Learning and Artificial Intelligence: Introduction artificial intelligence and machine learning, advanced search, machine learning, supervised learning, game playing, speech recognition, computer vision, expert systems, application AI, mathematical theorem proving, natural language understanding, scheduling and planning, artificial neural networks, machine learning, building AI systems.

Reinforcement Learning: The reinforcement learning problem, multi-arm bandits, finite markov decision processes, dynamic programming, temporal-difference learning, eligibility traces, planning and learning with tabular methods, on- policy prediction with approximation, neuroscience, application and case studies.

Manufacturing Planning and Control: MPC system Define, MPC system Framework, Matching the MPC System with need of firm, MPC Classification, Evolution of MPC, Concluding Principle.


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