Training Mode | Regular | Fastrack | Crash |
---|---|---|---|
Classroom | Online | 4 Months (M,W,F or T,T,S Class) (3 Class in a week) |
2 Months (Monday to Friday Class) (5 Class in a week) |
1 Months (Monday to Friday Class) (5 Class in a week 1:30 hour duration) |
Next G Classes offers an intensive Advance Python Expert Course designed to equip participants with in-depth knowledge and practical skills in Python programming and data science. This course is structured into two comprehensive modules, each focusing on essential aspects of Python and its applications.
Module 1: In this, participants embark on a journey from foundational Python concepts to advanced techniques. They start with Python basics, covering syntax, data types, control structures, and functions. As they progress, they delve into Advanced Python topics such as object-oriented programming (OOP), decorators, generators, and multithreading. This module ensures a solid understanding of Python's capabilities, preparing participants to write efficient and scalable code for diverse applications.
Module 2: It focuses on leveraging Python for Data Science, a critical skill in today's data-driven world. Participants learn SQL (Structured Query Language), essential for managing and querying databases. They gain proficiency in data manipulation and analysis using Python libraries such as NumPy, Pandas, Matplotlib, and Seaborn. Hands-on projects and case studies enable participants to apply their knowledge to real-world scenarios, mastering the entire data science workflow from data cleaning and preprocessing to visualization and statistical analysis.
At Next G Classes, the Advance Python Expert Course not only equips participants with technical expertise but also fosters problem-solving abilities and critical thinking in Python programming and data science. With industry-relevant curriculum, expert instructors, and practical learning experiences, graduates of this course are well-prepared to excel in roles requiring advanced Python skills and data science proficiency. Whether aiming to enter the tech industry or advance in their current career, this course provides the essential toolkit for success in the dynamic field of Python programming and data science.
Introduction to Languages
Python Software’s
Operators
Control Statements
Data Structures or Collections
List Collection
Tuple Collection
Set Collection
Dictionary Collection
Functions
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
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