The AI Bridge
Grow with AI. Learn from researchers around the world. The future of AI leadership isย inย yourย hands
Python for AI
Machine Learning
Deep Learning
Large Language Model
Research Methodology
We Create For You
AI Research Environment
๐ Learn from global AI researchers
๐ง Build real-world AI projects
๐ Join exclusive research seminars
๐งช Learn essential research methods
๐ค Connect with worldwide researchers
๐ Strengthen your higher study profile
๐ Top performers get research supervision
The AI Bridge
Course Module
Module 1
Machine Learning
What Youโll Learn
ย ย ย 
Introduction to Machine Learning
ย ย ย 
Data Understanding and Preprocessing
ย ย 
Feature Engineering
ย ย 
Supervised Learning โ Linear Regression / Logistic Regression / Classification Models: k-Nearest Neighbors / Decision Trees / Random Forests
ย ย 
Model Evaluation and Tuning โ Performance Metrics / Hyperparameter Optimization
ย ย 
Unsupervised Learning โ Clustering (K-Means) / Dimensionality Reduction (Principaln Component Analysis – PCA)
ย ย 
Support Vector Machines (SVM)
ย ย 
Model Deployment โ Deploying ML Models using Streamlit
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Hands-On Projects
ย ย 
Project 1: Supervised Learning
ย ย Project 2: Unsupervised Learning
โโโโโโโโ โโโโโโโโ
Exclusive Research Seminars
ย ย ย 
Seminar 1: AI Research Culture / Emerging Topics / Research Opportunities / Higher Study Guidance
ย ย ย 
Speaker: PhD Researcher 1
Module 2
Deep Learning
๐ What Youโll Learn
ย ย ย ๐ง Fundamentals of Neural Networks
ย ย ย ๐ Backpropagation and Optimization
ย ย ๐ ๏ธ Building Training Pipelines with PyTorch
ย ย ๐งฉ Convolutional Neural Networks (CNNs)
ย ย ๐งฌ Regularization and Transfer Learning
ย ย ๐ Recurrent Neural Networks (RNNs)
ย ย โ๏ธ Performance Tuning and Debugging
ย ย ๐ Model Evaluation and Interpretation
ย ย ๐พ Model Saving and Deployment with Streamlit
โโโโโโโโ โช โโโโโโโโ
๐งช Hands-On Projects
ย ย โ
Project 3: Building a Deep Learning Model for Image Recognition
ย ย โ
Project 4: Time Series Forecasting with RNNs
โโโโโโโโ โช โโโโโโโโ
๐ค Exclusive Research Seminars
ย ย ย ๐ Seminar 2: AI Research Culture / Emerging Topics / Research Opportunities / Higher Study Guidance
ย ย ย ๐ฉโ๐ Speaker: PhD Researcher 2
ย ย ย ๐ Seminar 3: AI Research Culture / Emerging Topics / Research Opportunities / Higher Study Guidance
ย ย ๐จโ๐ Speaker: PhD Researcher 3
Module 3
Large Language Models (GPT โข Gemini โข DeepSeek)
๐ What Youโll Learn
ย ย ย ๐ง Introduction to Large Language Models (LLMs)
ย ย ย โ๏ธ Anatomy of an LLM โ Transformers Recap: Attention & Self-Attention / Positional Encoding / Tokenization Techniques: BPE, WordPiece, SentencePiece
ย ย ย ๐ Text Generation with Pre-trained Models
ย ย ๐ฏ Prompt Engineering Strategies
ย ย ๐ง Fine-Tuning LLMs with Hugging Face
ย ย ๐ Retrieval-Augmented Generation (RAG)
ย ย ๐ค LLM Tools and Agents: LangChain
ย ย ๐ LLM App Development and Deployment with Streamlit
ย โโโโโโโโ โช โโโโโโโโ
๐งช Hands-On Project
ย ย ย โ
Project 5: LLM-Based Project
โโโโโโโโ โช โโโโโโโโ
๐ค Exclusive Research Seminar
ย ย ย ๐ Seminar 4: AI Research Culture / Emerging Topics / Research Opportunities / Higher Study Guidance
ย ย ย ๐จโ๐ Speaker: PhD Researcher 4
Module 1
Research Methodology ๐ Research in Practice
โ What is Research? โ Scientific vs. Applied Research
๐งญ Research Paradigms โ Qualitative / Quantitative / Mixed Methods
๐ค๏ธ The Research Process (Overview) โ From idea โ literature review โ design โ data collection โ analysis โ conclusion
๐ Formulating Research Questions โ Writing clear, focused, and researchable questions
๐ฌ Hypotheses โ Null vs. Alternative Hypotheses
๐งช Research Design Basics โ Exploratory / Descriptive / Experimental Designs
๐ฅ Data Collection Methods โ Surveys / Interviews / Observations
โ
Validity, Reliability & Ethics โ Ensuring quality and integrity in research
Python for AI
๐ This is an optional foundational course designed for students who do not have prior knowledgeย ofย Python.
โ Delivery: hands-on Google Colab notebooks, weekly quizzes, mini-projects
โ Goal: Build strong foundational Python skills for Machine Learning (ML) & Deep Learning (DL)
Course Module
๐ Introduction to Python and Programming Logic
๐งฎ Variables, Data Types and Type Conversion
๐ Control Flow โ Conditional Statements
๐ Loops โ For and While Loops
๐งฐ Functions and Code Reusability
๐ฆ Built-in Data Structures โ Lists, Tuples, Sets
๐ Dictionaries and Advanced Data Handling
๐ File Handling โ Reading and Writing Files
โ Error Handling and Exceptions
๐งฑ Introduction to Object-Oriented Programming (OOP)
๐งฌ OOP Concepts โ Inheritance and Encapsulation
๐งฎ External Libraries โ math, random, datetime
๐ข Introduction to NumPy for Numerical Computing
๐ Introduction to Pandas for Data Manipulation
๐ Introduction to Matplotlib for Data Visualization
๐ฆ Getting Started with PyTorch โ Tensors and Operations
Our Trainers
The AI Bridge
Python for AI
Price Details
๐ Python for AI
๐ฐ Total Fee: 8000 BDT-
Duration: 2 Months
-
Total Classes: 16
-
Payment Options
One-time payment offer: 7200 BDT (
Save 10%)
Pay in 2 monthly installments of 4000 BDT
โSave 0%
๐ค The AI Bridge
๐ฐ Total Fee: 30000 BDT-
Duration: 6 Months
-
Total Classes + Seminars: 48
-
Payment Options
๐น Pay in 2 monthly installments of 13500 BDT (during the first 2 months) โ ๐ฅ Save 10% (Total 27000 BDT)
๐น Pay in 3 monthly installments of 10000 BDT (during the first 3 months) โ Save 0%
๐ Combined Course
๐ฐ Combined Regular Fee: 38000 BDT-
Includes Python for AI + The AI Bridge
-
Duration: 8 Months
-
Total Sessions: 64
-
Bundle Payment Options
๐ Pay 30000 BDT for The AI Bridge (one-time payment)
๐ Get Python for AI absolutely FREE
๐ธ You save a full 8000 BDT
๐น Pay in 3 monthly installments of 12667 BDT (during the first 3 months) โ save 0%
๐น Pay in 2 monthly installments of 17100 BDT (during the first 2 months) โ
๐ฅ Save 10% (Total 34200 BDT)
Take Your Career to the Next Level!โ
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F.A.Q.
Do you have any questions? Please feel free to ask!
There are no strict academic requirements. However, you must be passionate, consistent, and committed, as this is a long-term course. A laptop and a stable internet connection are essential for participation.
- Fill out the registration form.
- Our representative will contact you shortly.
- You will have a discussion with one of our mentors to assess your motivation and eligibility.
- If approved, you will receive the bank details for payment.
- After your payment is confirmed, your seat in the upcoming batch will be reserved.
Once your discussion with a mentor is complete and you are approved, we will send you the bank details. You can then proceed with the first payment to confirm your seat in the course.
Mentors will assess your level of motivation and commitment. We are looking for students who are truly driven, curious, and ready to invest their time and energy into learning.
No, mentors are assigned based on their availability. However, we ensure that every batch receives guidance from experienced and high-quality mentors. Your learning experience will be in good hands.
Yes, you will continue to be part of our learning community even after completing the course. High-performing students may receive extra support, including opportunities for research supervision or publications. This is based on consistent effort, strong performance, and dedication during the course.
In general, we provide all necessary materials such as code, datasets, and practice resources. However, we do not share full course video recordings in order to maintain the integrity of our content. In special situations, such as medical emergencies, we may provide additional materials to help you stay on track.
We strongly encourage students to complete the course without breaks. In genuine emergency situations like medical issues, we may allow you to pause and rejoin later. However, if there is no valid reason, you may need to restart the course with a new batch and pay the full tuition fee again. While we aim to be flexible, our experience shows that too much flexibility can reduce students’ discipline and progress.
If you have any further questions, please feel freeย toย ask.