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Machine Learning with Python
Build intelligent models using Python and real-world data
Course Overview
Course Overview — Machine Learning with Python
The Machine Learning with Python course is a comprehensive, hands-on program designed to equip learners with the essential skills and knowledge required to analyze data and build intelligent, data-driven applications. This course is suitable for students, professionals, and aspiring data scientists who want to enter the field of machine learning using Python as the primary programming language.
The course begins with a strong foundation in Python programming for data science, ensuring learners are comfortable with core concepts and syntax. Participants are introduced to essential libraries such as NumPy and Pandas for data manipulation, cleaning, and preprocessing. Emphasis is placed on understanding real-world datasets and preparing them for analysis through effective data handling techniques.
Learners then explore Exploratory Data Analysis (EDA) using visualization tools like Matplotlib and Seaborn to uncover patterns, trends, and insights within data. This stage helps build analytical thinking and prepares students for model development by understanding data behavior and feature relationships.
The core of the course focuses on machine learning fundamentals, covering both supervised and unsupervised learning techniques. Participants learn key algorithms such as linear regression, logistic regression, decision trees, k-nearest neighbors (KNN), support vector machines (SVM), and clustering methods like k-means. Each algorithm is explained conceptually and implemented practically using Scikit-learn, enabling learners to understand how models work internally and how to apply them effectively.
The program also emphasizes model training, evaluation, and optimization. Students learn how to split datasets, measure model performance using appropriate metrics, avoid overfitting, and improve accuracy through parameter tuning. Practical exercises and projects help reinforce these concepts and simulate real-world problem-solving scenarios.
In addition, learners gain exposure to real-world machine learning applications, understanding how models are used in areas such as prediction, classification, and data-driven decision making. By the end of the course, participants will have developed the confidence and practical skills needed to work with machine learning models, analyze data effectively, and apply Python-based solutions to real business and industry problems.
What's Included in the Course
Course Syllabus
Explore the complete course syllabus to see what you'll learn from start to finish.
Week 1: Python & Data Science Foundations
- Python programming fundamentals
- Working with numerical data (NumPy)
- Data manipulation and analysis (Pandas)
- Creating visualizations
- Exploring and cleaning datasets
- Basic statistics
Week 2: Machine Learning Fundamentals
- What is Machine Learning and how it works
- Predicting numbers (Regression)
- Predicting categories (Classification)
- Measuring model performance
- Understanding different ML algorithms
- Splitting data for training and testing
Week 3: Intermediate Algorithms & Techniques
- Advanced prediction algorithms
- Combining multiple models (Ensemble methods)
- Working with text data
- Finding groups in data without labels (Clustering)
- Reducing complexity in data
- Understanding which features matter most
Week 4: Advanced Topics & Real-World Applications
- Creating better input features for models
- Handling tricky real-world data problems
- Optimizing model performance
- Introduction to neural networks
- Building complete ML systems
- Preparing models for use
Need More Information About This Course?
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Frequently Asked Questions
Code IT is a professional IT training institute that offers both online and offline courses in various fields like Web Development, Networking, Graphic Design, and more.
Yes, you will receive a certificate upon successful completion of the course.
Internship opportunities are available for most students; however, some courses do not include internships.
Yes, we offer job placement support. Terms and conditions apply.
Yes, the course fee must be paid during registration to confirm your seat.
Yes, demo classes are available. You can find them at the top of this syllabus — click the "Watch Demo" button.
Yes, you will get access to recorded class videos, which you can watch anytime with lifetime access.
Yes, Code IT provides lifetime support to all students, even after course completion.
No, the fee is non-refundable. However, you can transfer to another class if you inform the administrator within 1 day of the course start date.
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