AI & Machine Learning With Python
About Course
Course by:
IT Business Incubator, CUET
Chattogram-4349, Bangladesh.
Phone:
+88 01978-464904, +88 01601-063910
For More Details:
Learn by this Course
By the end of this course, participants will:
- Gain proficiency in essential AI concepts, including machine learning, NLP, and computer vision, to enhance employability
- Develop foundational skills in probability, statistics, basic linear algebra, and programming necessary for AI applications.
- Engage in in-depth sessions covering AI fundamentals, machine learning algorithms, NLP techniques, and computer vision principles.
- Apply acquired knowledge and skills to real-world problems through a capstone project, preparing for internships and job opportunities in the AI industry.
Schedule (Phase - 02)
Batch – 01: Friday & Saturday 10 am to 1 pm
Batch – 02: Friday & Saturday 3 pm to 6 pm
Pre-requisites
- Basic knowledge of probability and statistics
- A foundation in linear algebra
- Basic programming knowledge in Python
Course Coordinator:
Dr. M. Moshiul Hoque
Professor, Dept of CSE, CUET
Director, IT Business Incubator in CUET
Former Dean, Faculty of Electrical & Computer Engineering, CUET
Chair, IEEE Bangladesh Section
Trainers
1. MD. Asif Iqbal
Sr. Assessment developer, Workera.ai
Head of R&D, Diligite Ltd
Trainer, BDSET Project (AI & ML), BHTPA.
2. Dipon Talukder
Sr. Assessment Developer, Workera.ai
Lecturer, Dept. of CSE, East Delta University
Trainer, EDGE IICT CUET DST
3. Fatima Jahara
Alpha Testing Consultant, DeepLearning.AI
4. Md. Al-Mamun Provath
Lecturer, Dept. of CSE, CUET
Course Modules
This course is divided into the following six modules to address the concept of AI better.
1) AI & ML Essentials
2) Artificial Intelligence
3) Machine Learning
4) Natural Language Processing (NLP)
5) Computer Vision
6) Capstone Project
Book Recommendation:
1) The Hundred-Page Machine Learning Book by Andriy Burkov
2) Hands-On Computer Vision with TensorFlow 2: Leverage deep learning to create powerful image processing apps with TensorFlow 2.0 and Keras, by Benjamin Planche, Eliot Andres.
FAQ
1. Who Can Enroll in This Course?
This course is designed for individuals interested in pursuing a career in Artificial Intelligence and
Machine Learning. Ideal participants should have:
- Basic knowledge of probability and statistics
- A foundation in linear algebra
- Basic programming knowledge in Python
2. Who are the trainers for the course?
3. Is the course offered online or offline?
4. Are there any specific qualifications required to enroll in the course?
5. Will class recordings be available?
6. What type of certificate will be awarded upon course completion?
7. Is a waiver available, and how can I apply ? What percentage can I expect?
Yes, waivers are available. To apply, accurately fill Waiver Application form and submit it. After submission, you will need to take an online assessment test. Based on your application, CV, and assessment results, waivers ranging from 20% to 30% may be granted.
8. How can I enroll?
You can enroll either online through our website (www.itbi-cuet.com) or by visiting the office directly. Register on our website and select your desired course by clicking the ‘Add to Cart’ button. If you have a waiver coupon, apply it before confirming your cart. Then, proceed to checkout and complete your payment using the SSLCommerz gateway. For detailed instructions, please refer to the file: Enrollment Process.
9. Can I enroll in multiple courses?
Yes, you can enroll in multiple courses. However, please ensure that the schedules of the courses do not overlap.
10. Can I switch from online to offline batches or vice versa?
Generally, batch changes are not permitted. However, you may contact the authorities for special circumstances to discuss your request.
11. I live far from CUET; is there accommodation available for offline batch students?
Generally, batch changes are not permitted. However, you may contact the authorities for special circumstances to discuss your request.
Course Content
The Pre-Requisites Session
-
Class 01| 23 November 2024
02:15:53 -
Class 02 Part 01| 24 November 2024
01:18:28 -
Class 02 Part 02| November 2024
36:15
Artificial Intelligence
AI and ML Essentials
Machine Learning
Computer Vision
Capstone Project
Introduction to Python
Introduction to Advanced Python and Preparatory Classes on Python for AI & ML
Data Preprocessing and Data Visualization with Python
Machine Learning Introduction and Learning Paradigms
Student Ratings & Reviews
