PYTHON with MACHINE LEARNING
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Course Description
This course teaches Python with Machine Learning using real datasets.
You will learn data analysis, model building, and prediction techniques.
The program focuses on practical projects and industry use cases.
It prepares you for careers in data science and machine learning.
What You Will Learn
- Basic knowledge of computers
- Laptop or PC with internet connection
- No prior ML experience required
- Interest in data analysis and problem-solving
Course Curriculum
10 Sections• Python Architecture & Environment Setup
• Variables, Data Types & Operators
• Control Structures & Loops
• Functions, Modules & Packages
• Object-Oriented Programming (OOP) in Python
• Exception Handling & File Handling
• List, Set & Dictionary Comprehensions
• Lambda Functions & Functional Programming
• Decorators & Generators
• Working with APIs & JSON
• Virtual Environments & Dependency Management
• NumPy for Numerical Computing
• Pandas for Data Manipulation & Analysis
• Data Cleaning & Preprocessing Techniques
• Matplotlib & Seaborn for Visualization
• Exploratory Data Analysis (EDA)
• Descriptive & Inferential Statistics
• Probability Distributions
• Hypothesis Testing
• Linear Algebra Basics
• Optimization Concepts for ML
• Machine Learning Concepts & Workflow
• Supervised vs Unsupervised Learning
• Model Training, Validation & Testing
• Bias-Variance Trade-off
• Performance Metrics & Evaluation
• Linear & Multiple Regression
• Logistic Regression
• K-Nearest Neighbors (KNN)
• Decision Trees & Random Forest
• Support Vector Machines (SVM)
• Ensemble Learning Techniques
• Clustering Techniques (K-Means, Hierarchical)
• Dimensionality Reduction (PCA)
• Anomaly Detection
• Association Rule Mining
• Feature Engineering
• Hyperparameter Tuning
• Cross-Validation Techniques
• Model Persistence (Pickle / Joblib)
• Introduction to Model Deployment (Flask / FastAPI)
• Neural Network Fundamentals
• Introduction to TensorFlow & Keras
• Basic ANN Models
• Overview of CNN & RNN
• End-to-End Machine Learning Project
• Predictive Analytics Application
• Classification & Regression Use Cases
• Real Industry Datasets & Business Scenarios
Frequently Asked Questions
Testimonials
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"The trainers provided step-by-step explanations with real examples. Certification and career support gave me confidence to apply for jobs."
"Course structure was well organized and industry focused. Mock interviews and guidance sessions prepared me for real company roles."
"Learning experience was smooth and professional. Support team responded quickly and helped me throughout the training program."
"WebProtech gave me real industry skills with hands-on training. The projects helped me gain confidence."
"The teaching style is simple and clear. I was able to switch my career into IT easily."
"Best place to learn full stack development. Trainers focus on practical learning and doubt solving."
"I loved the structured course and real-time projects. It helped me understand concepts deeply."
"WebProtech helped me improve my coding skills. The DSA training was very useful for interviews."
"Support from mentors is great. They guide you at every step and help with placement preparation."
"Very good learning environment. The course content is updated and industry-focused."
"I joined as a beginner and now I can build full stack applications. Highly recommended institute."
"The best part is hands-on practice. You don’t just learn theory, you actually build projects."
Recent Placements
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Frequently Asked Questions
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