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MACHINE LEARNING

The SmartED Machine Learning Program is a comprehensive two-month course tailored for aspiring machine learning practitioners. In the first month, participants engage in interactive training sessions led by industry experts, covering fundamental concepts, algorithms, and tools in machine learning. The second month emphasizes practical application through hands-on projects, where learners collaborate on real-world challenges, including minor and major projects. Successful completion of the program awards participants with a course completion certificate and an internship completion certificate, making it an excellent opportunity for those looking to advance their careers in machine learning.

Course Instructors SmartED Innovations SmartED

₹4130.00 ₹5500.00 25% OFF

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Course Overview

Duration: 2 Months

Format: Hybrid (Live/Recorded Training & Hands-On Projects)


Month 1: Training with Industry Mentors

  • Objective: Gain foundational knowledge and insights from experienced professionals.
  • Format: A combination of live sessions and recorded content, providing flexibility for participants.


Key Components:

  • Live Sessions: Interactive lectures and Q&A with top industry mentors covering essential topics relevant to the field.
  • Recorded Content: Access to pre-recorded sessions for flexible learning at your own pace.
  • Topics Covered: Current industry trends, best practices, technical skills, and soft skills development.


Month 2: Hands-On Project Experience

  • Objective: Apply learned concepts through practical experience.


Key Components:

  • Live Research and Development Projects: Participants will engage in both minor and major projects, working on real-world challenges.
  • Collaboration: Work in teams to foster collaboration, problem-solving, and innovation.
  • Mentorship: Continuous support and guidance from industry mentors throughout the project phase.


Certification

Upon successful completion of the program, participants will receive:

  • Course Completion Certificate: Recognizing the completion of the training and project components.
  • Collaborated Internship Completion Certificate: Validating the hands-on experience gained during the program.


Schedule of Classes

Start Date & End Date

Sep 25 2024 - Nov 25 2024

Course Curriculum

1 Subject

MACHINE LEARNING

12 Exercises30 Learning Materials

Module1

1 _ML_ Introduction to Python

Video
31:56

2_ML_Introducion to ML

Video
47:22

3_ML_part_2

Video
1:2:43

ML Quiz 1

Exercise

Module 2

4_ML_4th-Supervised ---4.1

Video
58:12

5_ML_4th-Supervised ---4.2

Video
53:21

6_ML_4th-Supervised ---4.3

Video
1:2:45

ML Quiz 2

Exercise

Module 3

7_ML_4th-Supervised ---4.4

Video
49:45

8_ML-4th-Supervised ---4.5

Video
56:39

9_ML-4th-Supervised ---4.6

Video
57:52

MLQuiz 3

Exercise

Module 4

10_ML-4th-Supervised ---4.7

Video
56:26

11_ML-4th-Supervised ---4.8

Video
49:45

12_ML-4th-Supervised ---4.9

Video
55:16

ML Quiz 4

Exercise

Module 5

13 ML-4th-Supervised ---4.10

Video
58:56

14 ML-4th-Supervised ---4.11

Video
51:44

15 ML-4th-Supervised ---4.12

Video
51:45

ML Quiz 5

Exercise

Module 6

16 ML-4th-Supervised ---4.13

Video
55:23

17 ML-UN-Supervised -- 1

Video
52:29

18 ML-UN-Supervised -- 2

Video
51:48

ML Quiz 6

Exercise

Module 7

19 ML-UN-Supervised -- 3

Video
51:00

20 ML-UN-Supervised -- 4

Video
51:21

21 ML agents

Video
54:39

ML Quiz 7

Exercise

Module 8

22 ML Neural Networks Intro

Video
53:22

23 ML Neural Network Arc

Video
52:57

24 ML MultiLayer NNA

Video
51:47

MACHINE LEARNING Quiz 8

Exercise

Module 9

25 ML Deep Learning

Video
52:29

26 ML Intro to NLP

Video
52:37

27 ML Text Pre-Processing P-1

Video
51:34

MACHINE LEARNING Quiz 9

Exercise

Module 10

28 ML Text Pre-Processing P-2

Video
54:2

29 ML Advanced Neural net

Video
1:1:29

30 ML NPL final

Video
54:19

MACHINE LEARNING Quiz 10

Exercise

PROJECTS

MACHINE LEARNING Minor Projects

Assignment

MACHINE LEARNING Major Project

Assignment

Course Instructor

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SmartED Innovations

30 Courses   •   7131 Students


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SmartED

1 Courses   •   20 Students