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Courses / AI Academy / Machine Learning with Python
📘 Beginner ⏱ 45 Hours

Machine Learning with Python

🚀 Course Overview

Machine Learning with Python āĻšāϞ⧋ āĻāĻ•āϟāĻŋ 45 Hours Comprehensive & Project-Based Course, āϝ⧇āĻ–āĻžāύ⧇ āφāĻĒāύāĻŋ Python Programming āĻŦā§āϝāĻŦāĻšāĻžāϰ āĻ•āϰ⧇ Machine Learning Models āϤ⧈āϰāĻŋ, Train, Evaluate āĻāĻŦāĻ‚ Deploy āĻ•āϰāĻžāϰ Practical Skills āĻ…āĻ°ā§āϜāύ āĻ•āϰāĻŦ⧇āύāĨ¤

āĻŦāĻ°ā§āϤāĻŽāĻžāύ⧇ Machine Learning (ML) āĻšāϞ⧋ Artificial Intelligence-āĻāϰ āĻ…āĻ¨ā§āϝāϤāĻŽ āϗ⧁āϰ⧁āĻ¤ā§āĻŦāĻĒā§‚āĻ°ā§āĻŖ āĻļāĻžāĻ–āĻž, āϝāĻž Data Analysis, Prediction, Recommendation Systems, Fraud Detection, Healthcare, Finance āĻāĻŦāĻ‚ Business Intelligence-āĻ āĻŦā§āϝāĻžāĻĒāĻ•āĻ­āĻžāĻŦ⧇ āĻŦā§āϝāĻŦāĻšā§ƒāϤ āĻšāĻšā§āϛ⧇āĨ¤ āĻāχ āϕ⧋āĻ°ā§āϏ⧇ āφāĻĒāύāĻŋ Python, NumPy, Pandas, Matplotlib, Scikit-learn āĻāĻŦāĻ‚ āĻ…āĻ¨ā§āϝāĻžāĻ¨ā§āϝ āϜāύāĻĒā§āϰāĻŋāϝāĻŧ ML Libraries āĻŦā§āϝāĻŦāĻšāĻžāϰ āĻ•āϰ⧇ Real-world Projects-āĻāϰ āĻŽāĻžāĻ§ā§āϝāĻŽā§‡ Machine Learning āĻļāĻŋāĻ–āĻŦ⧇āύāĨ¤

āϕ⧋āĻ°ā§āϏāϟāĻŋ āĻāĻŽāύāĻ­āĻžāĻŦ⧇ āĻĄāĻŋāϜāĻžāχāύ āĻ•āϰāĻž āĻšāϝāĻŧ⧇āϛ⧇ āϝāĻžāϤ⧇ āφāĻĒāύāĻŋ Theory-āĻāϰ āĻĒāĻžāĻļāĻžāĻĒāĻžāĻļāĻŋ Hands-on Practice-āĻāϰ āĻŽāĻžāĻ§ā§āϝāĻŽā§‡ Industry-ready Skills āĻ…āĻ°ā§āϜāύ āĻ•āϰāϤ⧇ āĻĒāĻžāϰ⧇āύāĨ¤

Basic Python Programming Knowledge Required.


📚 Course Information

  • Course Name: Machine Learning with Python
  • Duration: 45 Hours
  • Level: Beginner to Intermediate
  • Language: Bangla + English
  • Class Type: Online / Offline
  • Prerequisite: Basic Python Programming & Basic Mathematics
  • Hands-on Practice: Yes
  • Real-world Projects: Yes
  • Certificate: Yes

đŸŽ¯ What You’ll Learn

āĻāχ āϕ⧋āĻ°ā§āϏ⧇ āφāĻĒāύāĻŋ āĻļāĻŋāĻ–āĻŦ⧇āĻ¨â€”

✅ Python for Machine Learning

✅ Data Collection & Data Preprocessing

✅ NumPy & Pandas

✅ Data Visualization with Matplotlib

✅ Introduction to Machine Learning

✅ Supervised Learning

✅ Unsupervised Learning

✅ Regression Algorithms

✅ Classification Algorithms

✅ Clustering Techniques

✅ Model Training & Evaluation

✅ Feature Engineering

✅ Hyperparameter Tuning

✅ Scikit-learn Library

✅ Real-world Machine Learning Projects

✅ Model Deployment Basics


📖 Course Modules

Module 1 – Python for Data Science

  • Python Refresher
  • NumPy Fundamentals
  • Pandas for Data Analysis
  • Data Cleaning
  • Data Manipulation

Module 2 – Data Visualization

  • Matplotlib
  • Data Visualization Techniques
  • Exploratory Data Analysis (EDA)
  • Understanding Patterns in Data

Module 3 – Introduction to Machine Learning

  • What is Machine Learning?
  • Types of Machine Learning
  • ML Workflow
  • Preparing Datasets

Module 4 – Supervised Learning

  • Linear Regression
  • Logistic Regression
  • Decision Trees
  • Random Forest
  • K-Nearest Neighbors (KNN)
  • Support Vector Machine (SVM)

Module 5 – Unsupervised Learning

  • K-Means Clustering
  • Hierarchical Clustering
  • Dimensionality Reduction
  • Principal Component Analysis (PCA)

Module 6 – Model Evaluation

  • Train/Test Split
  • Cross Validation
  • Accuracy, Precision & Recall
  • Confusion Matrix
  • Model Optimization

Module 7 – Feature Engineering & Deployment

  • Feature Selection
  • Feature Scaling
  • Hyperparameter Tuning
  • Saving Models
  • Model Deployment Basics

Module 8 – Real-world Projects

  • House Price Prediction
  • Customer Churn Prediction
  • Sales Forecasting
  • Spam Email Detection
  • Student Performance Prediction
  • Final Machine Learning Project

👨‍đŸ’ģ Who Should Join?

āĻāχ āϕ⧋āĻ°ā§āϏāϟāĻŋ āĻŦāĻŋāĻļ⧇āώāĻ­āĻžāĻŦ⧇ āωāĻĒāϝ⧋āĻ—ā§€â€”

  • Students
  • Python Developers
  • Data Analysts
  • Aspiring Data Scientists
  • AI & ML Enthusiasts
  • Software Engineers
  • Researchers
  • IT Professionals
  • Freelancers
  • Anyone interested in Machine Learning

🎓 After Completing This Course

āĻāχ āϕ⧋āĻ°ā§āϏ āĻļ⧇āώ āĻ•āϰāĻžāϰ āĻĒāϰ āφāĻĒāύāĻŋ āĻĒāĻžāϰāĻŦ⧇āĻ¨â€”

  • Python āĻŦā§āϝāĻŦāĻšāĻžāϰ āĻ•āϰ⧇ Machine Learning Models āϤ⧈āϰāĻŋ āĻ•āϰāϤ⧇āĨ¤
  • Real-world Dataset Analyze āĻ“ Preprocess āĻ•āϰāϤ⧇āĨ¤
  • Regression, Classification āĻāĻŦāĻ‚ Clustering Algorithms āĻŦā§āϝāĻŦāĻšāĻžāϰ āĻ•āϰāϤ⧇āĨ¤
  • Data Visualization āĻ“ Feature Engineering āĻ•āϰāϤ⧇āĨ¤
  • Machine Learning Models Evaluate āĻ“ Optimize āĻ•āϰāϤ⧇āĨ¤
  • Scikit-learn āĻŦā§āϝāĻŦāĻšāĻžāϰ āĻ•āϰ⧇ End-to-End ML Projects āϤ⧈āϰāĻŋ āĻ•āϰāϤ⧇āĨ¤
  • Basic Model Deployment āϏāĻŽā§āĻĒāĻ°ā§āϕ⧇ āϧāĻžāϰāĻŖāĻž āĻ…āĻ°ā§āϜāύ āĻ•āϰāϤ⧇āĨ¤
  • Data Science āĻ“ AI Career-āĻāϰ āϜāĻ¨ā§āϝ Strong Foundation āϤ⧈āϰāĻŋ āĻ•āϰāϤ⧇āĨ¤

đŸ’ŧ Practical Projects

  • House Price Prediction Model
  • Sales Forecasting System
  • Customer Churn Prediction
  • Spam Email Classifier
  • Student Result Prediction
  • Customer Segmentation
  • Recommendation System (Basic)
  • Final End-to-End Machine Learning Project