Training Mode | Regular | Fastrack | Crash |
---|---|---|---|
Classroom | Online | 6 Months (M,W,F or T,T,S Class) (3 Class in a week) |
3 Months (Monday to Friday Class) (5 Class in a week) |
2 Months (Monday to Friday Class) (5 Class in a week 1:30 hour duration) |
The Advance Python Expert Course at Next G Classes is meticulously crafted for individuals aiming to master both foundational and advanced aspects of Python programming, as well as dive into the dynamic field of data science. This comprehensive program is divided into two modules, each targeting essential skills and knowledge areas.
Module 1: Python Basic Course & Python Advance Course This module starts with the essentials of Python programming, ensuring a solid understanding of core concepts. Participants learn the basics of Python, covering syntax, data types, control structures, functions, and modules. As the course progresses, the curriculum delves into advanced Python topics, including object-oriented programming, file handling, exception handling, and advanced data structures. This rigorous module equips students with the skills needed to write efficient and scalable Python code, laying a strong foundation for more complex applications and developments.
Module 2: Data Science In the second module, participants transition to the exciting realm of data science. The module begins with SQL, an essential tool for data manipulation and database management. Participants learn how to query databases, manage data, and perform complex data operations using SQL. Building on this, the course covers key data science concepts such as data cleaning, data analysis, and data visualization. Students gain hands-on experience with data science libraries and tools, applying their skills to real-world datasets and projects.
Throughout the Advance Python Expert Course at Next G Classes, a blend of theoretical knowledge and practical application ensures that participants gain comprehensive expertise. By the end of the course, graduates are proficient in Python programming and well-versed in data science techniques, ready to tackle challenging roles in the tech industry.
Overview of Databases
Introduction to SQL
Basic SQL Commands
Database Schema
Hands-on Practice
Advanced Querying Techniques
Joins and Subqueries
Aggregate Functions and Grouping
Data Manipulation
Hands-on Practice
Stored Procedures and Functions
Triggers and Views
Performance Tuning and Optimization
Database Security
Data Warehousing and Analytics
Hands-on Practice
SQL in Different Database Management Systems
Advanced Features in Specific DBMS
Database Migration and Integration
Hands-on Practice
Module: 1
Module: 4 Overriding
Regular expressions
File &Directory handling
Date & Time module
OS module
Multi-threading & Multi Processing
Garbage collection
Python Data Base Communications (PDBC)
Python – Network Programming
Tkinter & Turtle