Core & Advanced Python Programmer Training Course

Acquire Key Python Skills: Master Programming, Earn Certification, Launch Your Dev Career! DevLustro Academy has established itself as a leader in Python programming, providing a comprehensive program that ensures participants develop, optimize, and utilize Python applications in ways never before imagined. DevLustro Academy has established itself as a leader in Python programming, providing a comprehensive program that ensures participants develop, optimize, and utilize Python applications in ways never before imagined. Course was selected for our collection of top-rated courses trusted by businesses worldwide.

Our Core Highlights

World Class Instructor
World Class Instructor Mentorship from global experts
1:1 with Industry Expert
1:1 with Industry Expert Personalised coaching tailored to you
Global Hiring Network
Global Hiring Network 400+ hiring partners around the world
Average Salary Hike
Average Salary Hike 55% average hike for our alumni

Course Description

The Core & Advanced Python Programmer course offers learners the opportunity to master one of the most versatile programming languages used in software development today. Get started with the dynamic field of Python programming and learn core and advanced Python concepts, including web development, data analysis, and machine learning, with the help of experienced instructors. Learners will emerge prepared to tackle real-world programming challenges. Here are some of the skills you will need to learn if you want to become a proficient Python programmer. The Core & Advanced Python Programmer course teaches you to master the concepts of Python programming. Through this comprehensive Python training, you will learn data analysis, machine learning, data visualization, web scraping, and natural language processing (NLP). Lambda Operator, Filter, Reduce, and Map Nested try-except-finally blocks The Core & Advanced Python Programmer Course is designed to teach essential Python programming skills, covering both fundamental and advanced concepts to prepare learners for a career in software development. This course is ideal for beginners new to Python programming, as well as professionals looking to enhance their skills and advance their careers in software development. There are no specific prerequisites for this course. A basic understanding of programming concepts and an interest in learning Python will be helpful, but not necessary. The course duration varies depending on the individual’s learning pace. On average, it can be completed in 8-10 weeks with a commitment of a few hours per week. You will learn the fundamentals of Python programming, including syntax, data types, control structures, object-oriented programming, advanced topics such as multithreading, data manipulation, and web development. Yes, upon successful completion of the course, you will receive a certification from DevLustro Academy, recognized worldwide. Yes, the course includes hands-on projects and assignments to provide practical experience. These projects are designed to help you apply the concepts learned in real-world scenarios. Yes, you will have lifetime access to the course materials, allowing you to revisit and review the content whenever needed. You will have access to personalized support from a course coordinator, feedback from trainers, and post-session availability of trainers for any additional help or questions. This course equips you with the skills and knowledge to excel in various Python programming roles, such as Python Developer, Data Scientist, and Machine Learning Engineer. It enhances your employability and career prospects in the rapidly growing field of software development. Course Audio Explanation (தமிழ்) Master the core concepts of Python programming, including syntax, data types, and control structures to build robust applications. Dive into advanced topics such as multithreading, decorators, and error handling to enhance your programming skills. Understand the principles of object-oriented programming (OOP) in Python, covering classes, objects, inheritance, and polymorphism. Harness powerful libraries like NumPy and Pandas for efficient data manipulation, analysis, and visualization. Learn the essentials of building dynamic web applications using frameworks like Django and Flask. Explore machine learning algorithms and artificial intelligence techniques using popular libraries like Scikit-learn and TensorFlow. In an increasingly digital world, the demand for smart, data-driven, and automated marketing solutions is rising at a breakneck pace.… Full Stack Developer Demand , Skills, and Compensation Introduction : The Strategic Importance of the Full-Stack Developer The full-stack developer—a… Introduction : 5 Surprising Truths About A Career in JavaScript Beyond the Code Web development is often seen as a… Master the essentials and advanced techniques of Python programming with our comprehensive Core & Advanced Python Training Course. Master the essentials and advanced techniques of Python programming with our comprehensive Core & Advanced Python Training Course. Unlock the power of online marketing with our Digital Marketing Fundamentals Training Course. Master SEO, SEM, content marketing. Invite friends to join our community, and receive valuable gift vouchers as a token of appreciation for each successful referral. Spread the word about our referral program today and start earning rewards! DevLustro Academy provides students with highly effective coaching classes, delivered through immersive classroom sessions and the best teaching methodologies designed to yield valuable results. We take great pride in our identity and are honored to be a part of your business journey. DevLustro Academy provides students with highly effective coaching classes, delivered through immersive classroom sessions and the best teaching methodologies designed to yield valuable results. We take great pride in our identity and are honored to be a part of your business journey. Copyright © DevLustro Academy | A Part of DevLustros

Course Goals

  • Core & Advanced Python Programmer Training Course
  • By Sundaresh Kamaraj
  • Programming Development Course
  • Course Details
  • Industry Based Projects
  • Personalized coordinator.
  • Trainer feedback.
  • Trainer availability post sessions.
  • Get your staff certified.
  • Certificate from governing bodies.
  • Recognized worldwide
  • Hands on assignment
  • Master Python fundamentals, including variables, data types, loops, and functions.
  • Dive into advanced concepts such as object-oriented programming (OOP) and error handling.
  • Harness powerful libraries like NumPy and Pandas for data manipulation and analysis.
  • Visualize data effectively using Matplotlib and Seaborn.
  • Implement machine learning algorithms with Scikit-learn.
  • Explore deep learning techniques with TensorFlow.
  • Python is the foundation that powers diverse applications from web development to data science.
  • Python programming involves the comprehensive development and optimization of software solutions.
  • Data Cleaning ensures that the data used for analysis is accurate and relevant.
  • Python Developers understand coding principles and derive meaningful solutions to complex problems.
  • Python is the substructure on which advanced technologies like Artificial Intelligence and Machine Learning are built.
  • Live, interactive training by experts.
  • Curriculum that focuses on the learner.
01Chapter-1 Introduction To Script
  • 01.01What is Script, program?
  • 01.02Types of Scripts
  • 01.03Difference between Script and Programming Languages
  • 01.04Features and Limitation of Scripting
  • 01.05Types of programming Language Paradigms
  • 01.06What is Python?
  • 01.07Why Python?
  • 01.08Who Uses Python?
  • 01.09Characteristics of Python
  • 01.10What is PSF?
  • 01.11History of Python
  • 01.12Python Versions
  • 01.13How to Download and Install Python
  • 01.14Install Python with Diff IDEs
  • 01.15Features and Limitations of Python
  • 01.16Creating Your First Python Program Python Applications
  • 01.17Printing to the Screen
  • 01.18Reading Keyboard Input
  • 01.19Using Command Prompt and GUI or IDE
  • 01.20Python Distributions
02Chapter-2 Different Modes In Python
  • 02.01Execute the Script
  • 02.02Interactive and Script Mode
  • 02.03Python File Extensions
  • 02.04SETTING PATH IN Windows
  • 02.05Clear screen inside python
  • 02.06Learn Python Main Function
  • 02.07Python Comments
  • 02.08Quit the Python Shell
  • 02.09Shell as a Simple Calculator
  • 02.10Order of operations
  • 02.11Multiline Statements
  • 02.12Quotations in Python
  • 02.13Python Path Testing
  • 02.14Joining two lines
  • 02.15Python Implementation Alternatives
  • 02.16Sub Packages in Python
  • 02.17Uses of Python in Data Science, IoT
  • 02.18Working with Python in Unix/Linux/Windows/Mac/Android..!!
  • 02.19PyCharm IDE
  • 02.20How to Work on PyCharm PyCharm Components
  • 02.21Debugging process in PyCharm PYTHON Install Anaconda
  • 02.22What is Anaconda? Coding Environments
  • 02.23Spyder Components General Spyder Features
  • 02.24Spyder Shortcut Keys
  • 02.25Jupyter Notebook
  • 02.26What is Conda? And Conda List?
  • 02.27Jupyter and Kernels
  • 02.28What is PIP?
03Chapter-3 Variables in Python
  • 03.01What is Variable?
  • 03.02Variables and Constants in Python
  • 03.03Variable, Variable names and Value
  • 03.04Mnemonic Variable Names Values and Types
  • 03.05What Does "Type" Mean?
  • 03.06Multiple Assignment
  • 03.07Python different numerical types Standard Data Types
  • 03.08Operators and Operands
  • 03.09Order of Operations Swap variables
  • 03.10Python Mathematics Type Conversion
  • 03.11Mutable Versus Immutable Objects
  • 03.12What is a data type?
  • 03.13Types of Data types
  • 03.14Numbers
  • 03.15List
  • 03.16Tuple
  • 03.17Strings
  • 03.18Dictionary
  • 03.19Sets
  • 03.20Lists are mutable
  • 03.21Getting to Lists
  • 03.22List indices
  • 03.23Traversing a list
  • 03.24List operations, slices and methods
  • 03.25Map, filter and reduce
  • 03.26Deleting elements
  • 03.27Lists and strings
  • 03.28Advantages of Tuple over List
  • 03.29Packing and Unpacking Comparing tuples
  • 03.30Creating nested tuple Using tuples as keys in dictionaries
  • 03.31Deleting Tuples Slicing of Tuple
  • 03.32Tuple Membership Test Built-in functions with Tuple
04Chapter-4 Dictionary
  • 04.01How to create a dictionary?
  • 04.02PYTHON HASHING? Python Dictionary Methods
  • 04.03Copying dictionary Updating Dictionary
  • 04.04Delete Keys from the dictionary Dictionary items() Method
  • 04.05Sorting the Dictionary Python Dictionary in-built Functions
  • 04.06Dictionary len() Method
  • 04.07Variable Types Python List cmp() Method
  • 04.08Dictionary Str(dict)
  • 04.09How to create a set?
  • 04.10Iteration Over Sets Python Set Methods
  • 04.11Python Set Operations Union of sets
  • 04.12Built-in Functions with Set
  • 04.13Python Frozenset
  • 04.14What is string?
  • 04.15String operations and indices Basic String Operations
  • 04.16String Functions, Methods
  • 04.17Delete a string
  • 04.18String Multiplication and concatenation
  • 04.19Python Keywords, Identifiers and Literals
  • 04.20String Formatting Operator
  • 04.21Structuring with indentation in Python
  • 04.22Built-in String Methods
05Chapter-5 Python operators
  • 05.01Arithmetic, Relational Operators and Comparison Operators
  • 05.02Python Assignment Operators Short hand Assignment Operators
  • 05.03Logical Operators or Bitwise Operators Membership Operators
  • 05.04Identity Operators Operator precedence
  • 05.05Evaluating Expressions
  • 05.06How to use "if condition" in conditional structures
  • 05.07if statement (One-Way Decisions)
  • 05.08if.. else statement (Two-way Decisions)
  • 05.09How to use "else condition"
  • 05.10if.. elif .. else statement (Multi-way)
  • 05.11When "else condition" does not work
  • 05.12How to use "elif” condition
  • 05.13How to execute conditional statement with minimal code
  • 05.14Nested IF Statement
06Chapter-6 Operators
  • 06.01What is an operator?
  • 06.02Different type of operators
  • 06.03Arithmetic Operators
  • 06.04Assignment operator
  • 06.05Unary minus operator
  • 06.06Relational operators
  • 06.07Logical operators
  • 06.08Membership operators
  • 06.09Identity operators
  • 06.10How to use "While Loop" and "For Loop"
  • 06.11How to use For Loop for set of other things besides numbers
  • 06.12Break statements, Continue statement, Enumerate function for For Loop
  • 06.13Practical Example How to use for loop to repeat the same statement over and again
  • 06.14Break, continue statements
07Chapter-7 Python Functions
  • 07.01What is a function?
  • 07.02How to define and call a function in Python
  • 07.03Types of Functions
  • 07.04Significance of Indentation (Space) in Python
  • 07.05How Function Return Value?
  • 07.06Types of Arguments in Functions
  • 07.07Default Arguments and Non-Default Arguments
  • 07.08Keyword Argument and Non-keyword Arguments
  • 07.09Arbitrary Arguments
  • 07.10Rules to define a function in Python
  • 07.11Various Forms of Function Arguments
  • 07.12Scope and Lifetime of variables
  • 07.13Nested Functions
  • 07.14Call By Value, Call by Reference
  • 07.15Anonymous Functions/Lambda functions
  • 07.16Passing functions to function
  • 07.17map(), filter(), reduce() functions
  • 07.18What is a Docstring?
  • 07.19Lambda Operator, Filter, Reduce, and Map
  • 07.20Lambda function
  • 07.21Filter function
  • 07.22Reduce function
  • 07.23Map function
08Chapter-8 List Comprehension
  • 08.01Introduction
  • 08.02Generator Comprehension
  • 08.03Set Comprehension
  • 08.04Importing module
  • 08.05Math module
  • 08.06Random module
  • 08.07Packages
  • 08.08Composition
  • 08.09Printing on screen
  • 08.10Reading data from keyboard
  • 08.11Opening and closing file
  • 08.12Reading and writing files
  • 08.13Functions
09Chapter-9 Exception Handling
  • 09.01Exception
  • 09.02Exception Handling
  • 09.03Except clause
  • 09.04Try...finally clause
  • 09.05User Defined Exceptions
  • 09.06Match function
  • 09.07Search function
  • 09.08Matching VS Searching
  • 09.09Modifiers
  • 09.10Patterns
10Chapter-10 Packages
  • 10.01Packages
  • 10.02Predefined Packages
  • 10.03User Defined
  • 10.04Packages File Handling
  • 10.05Text Files
  • 10.06Binary Files
  • 10.07Zip and Unzip Files
  • 10.08Pickling
  • 10.09Unpickling
  • 10.10Reading Program from another Program In Command Prompt
  • 10.11File Handling
  • 10.12Python File Handling
  • 10.13Python Read Files
  • 10.14Python Write/Create Files
  • 10.15Python Delete Files
11Chapter-11 Object Oriented Programming
  • 11.01What are Constructors
  • 11.02Is constructor mandatory in Python?
  • 11.03Can a constructor be called explicitly?
  • 11.04How many parameters can constructor have?
  • 11.05Parameterized and Non-Parameterized Constructors in Python
  • 11.06Difference between a method and constructor in Python
  • 11.07Difference between a method and a function
  • 11.08Types of Class Variables
  • 11.09Instance Variables
  • 11.10Where instance variables can be declared?
  • 11.11Accessing instance variables
  • 11.12Static Variables
  • 11.13Declaring static variables
  • 11.14Accessing a static variable
  • 11.15Local Variables
  • 11.16Types of Methods in a Class
  • 11.17Instance Methods
  • 11.18Setter and Getter methods
  • 11.19Class Methods
  • 11.20Static Methods
  • 11.21Nested Classes
  • 11.22Garbage Collection
  • 11.23Super() Function in Python
  • 11.24Which scenarios super() function is required?
  • 11.25Different Approaches for calling method of a specific super class.
  • 11.26Different cases for super() function
  • 11.27Polymorphism
  • 11.28Types of Polymorphism
  • 11.29Overloading
  • 11.30Operator Overloading
  • 11.31Method Overloading
  • 11.32How we can handle overloaded method requirements
  • 11.33Constructor Overloading
  • 11.34Overriding
  • 11.35Method Overriding
  • 11.36Constructor Overriding
  • 11.37What is an Abstract Class in Python?
  • 11.38Types of Methods in Python based on the Implementation
  • 11.39How to declare an abstract method in Python
  • 11.40Abstract Classes in Python
12Chapter-12 Exception Handling & Files
  • 12.01Exception Handling
  • 12.02Types of Error
  • 12.03Syntax and Runtime Errors
  • 12.04What is an Exception?
  • 12.05Exception Handling in Python
  • 12.06Finally Block
  • 12.07Why do we need Finally Block?
  • 12.08Finally Block in Python
  • 12.09Why not 'try except' block for clean-up activities?
  • 12.10Different control flow cases of try except finally in Python
  • 12.11Nested try-except-finally blocks
  • 12.12Nested try-except-finally blocks in Python
  • 12.13Different cases and scenarios
  • 12.14Else Block in Python
  • 12.15Possible Combinations with try-except-else-finally
  • 12.16Files
  • 12.17What is a File?
  • 12.18Types of Files
  • 12.19File Modes
  • 12.20Opening and Closing a File
  • 12.21Properties of File Object
  • 12.22Writing data to a File
  • 12.23Reading data From a File
  • 12.24With Keyword
13Chapter-13 Multithreading
  • 13.01What is Multitasking?
  • 13.02Process based and Thread based Multitasking
  • 13.03Applications of Multithreading
  • 13.04How to implement Multithreading?
  • 13.05Different Ways to Create a Thread
  • 13.06Creating a Thread using Thread class
  • 13.07Creating a Thread class by inheriting Thread class
  • 13.08active_count()
  • 13.09enumerate()
  • 13.10isAlive()
  • 13.11join()
  • 13.12join(seconds)
  • 13.13Synchronization
  • 13.14How to implement synchronization?
  • 13.15Synchronization By using Lock concept
  • 13.16Synchronization By using RLock concept
  • 13.17Difference between Lock and RLock
  • 13.18Synchronization by using Semaphore
  • 13.19Bounded Semaphore
  • 13.20What is Inter Thread communication?
  • 13.21Inter Thread communication by using Event Objects
  • 13.22Inter Thread communication by using Condition Object
  • 13.23Inter Thread communication by using Queue in Python
  • 13.24Types of Queues
  • 13.25FIFO Queue
  • 13.26LIFO Queue
  • 13.27Priority Queue
14Chapter-14 Base Communication and Networking
  • 14.01What is XML?
  • 14.02Difference between XML and HTML and XML, JSON, Gson
  • 14.03How to Parse XML and Create XML Node www
  • 14.04Python vs JAVA
  • 14.05XML and HTML
  • 14.06What is Database?
  • 14.07Types of Databases?
  • 14.08What is DBMS?, RDBMS?
  • 14.09What is Big Data?
  • 14.10Types of data?
  • 14.11Oracle MySQL
  • 14.12SQL server
  • 14.13Postgres SQL Executing the Queries
  • 14.14Bind Variables Installing of Oracle Python Modules
  • 14.15What is testing?
  • 14.16Types of Testing and Methods?
  • 14.17What is Unit Testing?
  • 14.18What is PyUnit?
  • 14.19Test scenarios, Test Cases, Test suites
  • 14.20Socket
  • 14.21Socket Module
  • 14.22Methods
  • 14.23Client and server
  • 14.24Internet modules
15Chapter-15 Packages
  • 15.01Introduction to numpy
  • 15.02Creating arrays o Indexing Arrays
  • 15.03Array Transposition
  • 15.04Universal Array Function
  • 15.05Array Processing
  • 15.06Array Input and Output
  • 15.07What are pandas?
  • 15.08Where it is used?
  • 15.09Series in pandas
  • 15.10Index objects
  • 15.11Reindex
  • 15.12Drop Entry
  • 15.13Selecting Entries
  • 15.14Data Alignment
  • 15.15Rank and Sort
  • 15.16Summary Statics
  • 15.17Index Hierarchy
  • 15.18Data Visualization
  • 15.19Python for Data Visualization
  • 15.20Welcome to the Data Visualization Section
  • 15.21Introduction to Matplotlib
16Chapter-16 Data Science
  • 16.01What is Data Science?
  • 16.02Data Science Life Cycle?
  • 16.03What is Data Analysis, Data Mining?
  • 16.04Analytics vs Data Science
  • 16.05IMPACT OF THE INTERNET
  • 16.06What is IOT
  • 16.07History of IoT
  • 16.08What is Network, Protocol, smart?
  • 16.09How IoT Works?
  • 16.10The Future of IoT

No FAQ added yet.

Ready to begin?

Core & Advanced Python Programmer Training Course

Duration: 45 Hours

Enroll in

Core & Advanced Python Programmer Training Course

Want to know more?