Level
Beginner
Course Fee
USD 100
Age Group
Above 16 Years
Prerequisite
Basic familiarity with programming
Description
This course provides a comprehensive journey through Python programming, starting with the basics and progressing through data processing, machine learning, and deep learning.
Course Features
Comprehensive Curriculum: The course spans Python basics to advanced deep learning topics, making it suitable for beginners and intermediate learners.
Industry-Relevant Tools: Learners will work with popular tools like Pandas, NumPy, Scikit-learn, and TensorFlow, gaining experience with real-world applications.
Hands-on Projects: Each module is complemented by practical assignments that reinforce learning and ensure skill development.
Course Outline
| Lecture | Topic | Sub Topic |
|---|---|---|
| Lecture 1 | Python Basics | Basic Operators |
| Lecture 2 | Python Basics | Basic Data Types |
| Lecture 3 | Python Basics | Control Structures (conditions and loops) |
| Lecture 4 | Python Basics | Functions |
| Lecture 5 | Python Basics | Object Oriented Programming Basics |
| Lecture 6 | Data Processing | Pandas for Tabular Data Manipulation |
| Lecture 7 | Data Processing | Matplotlib for Data Visualization |
| Lecture 8 | Data Processing | NumPy for Numerical Computations |
| Lecture 9 | Machine Learning | Supervised Classification |
| Lecture 10 | Machine Learning | Supervised Regression |
| Lecture 11 | Machine Learning | Unsupervised Dimension Reduction |
| Lecture 12 | Machine Learning | Unsupervised Clustering |
| Lecture 13 | Deep Learning | Optimization and Generalization |
| Lecture 14 | Deep Learning | DNN for Classification and Regression |
| Lecture 15 | Deep Learning | CNN for Image Classification |
| Lecture 16 | Deep Learning | Transformers for Sequence Classification |
Why Should You Enroll in this Course?
This course is uniquely structured to take learners from foundational Python programming to the cutting edge of machine learning and deep learning. It offers a balanced mix of theory and practical applications, ensuring learners not only understand the concepts but can also apply them to solve real-world problems.
Certificate
Final Project Completion
90% Attendance
Schedule
Classes per Week: 2
Duration: 8 weeks (16 lectures)
Days/Timing: Teacher will decide with the student
Instructor
