About The Course
This comprehensive course is designed to provide an in-depth understanding of Python programming and its application in the field of machine learning. Starting from the basics of Python, the course progresses to cover advanced topics such as data preprocessing, feature engineering, model selection, and evaluation. Through a series of hands-on projects and real-world examples, you will learn how to build, train, and deploy machine learning models using popular libraries such as Scikit-Learn, TensorFlow, and Keras. Whether you are a beginner looking to break into the field or an experienced programmer seeking to enhance your skills, this course offers valuable insights and practical knowledge.
Key Features:
- Introduction to Python and its libraries for data science
- Comprehensive coverage of machine learning algorithms
- Hands-on projects and case studies
- Guidance on best practices and industry standards
- Access to a supportive online community and resources
What Will You Learn?
Python Programming
Data Analysis with Python
Introduction to Machine Learning
Advanced Machine Learning Techniques
Deep Learning
Course Curriculam
Python Introduction
Required Softwares
06:16Introduction
11:50Arithmetic Operators
05:05Handling Strings and Raw String
07:26String Operations
06:00List and List Operations
11:35Tuples
05:22Sets
09:39Addition , User input and conversion
06:28Average Calculation Program
05:30Time Conversion – Integer Division – Modulo Division
05:19Report Generation – Formatted Output
09:28Salary Program
08:04Even or Odd – if else
05:21Larger between two numbers – if else
03:17Eligible to Vote or Not – if else
03:27Vowel or Consonant – if else
05:22Largest Among Three Numbers – Nested If Else
10:04Weekday Program – elif (if – else ladder)
03:41Type Of Vowel Program – elif (if else ladder) Logical Operator
03:43Iterative Statement – for loop
06:34Iterative Statement – while loop
07:31
Kamakshi Srimal
3 months ago