ACLM Institute of Professional Studies

Advanced Python Training - Online Courses & Certifications

06 MonthsOnline / OfflineIntermediateACLM CertificationACLM Certification

COURSE OVERVIEW

Course Overview

Advanced Python Training - Online Courses & Certifications is a six-month, intermediate-level online programme from ACLM Institute of Professional Studies. It develops practical capability in advanced Python programming, data analysis, data handling, database connectivity, operating-system services, network programming, graphical interfaces, modular application design, testing and concurrent programming. The programme follows instructor-led, one-to-one and group-training approaches, supported by notes, assignments and e-books from ACLM.

WHY THIS COURSE

Why Learn This Course?

Python is widely used for programming, automation, data analysis, web services and application development. This course helps learners move beyond basic syntax and build structured, testable and practical Python solutions. With a planned balance of conceptual learning and hands-on work, learners practise advanced programming patterns and apply Python to data mining, data analysis and customisation tasks.

LEARNING OUTCOMES

What You Will Learn

Refresh and strengthen core Python programming concepts.
Work confidently with Python data types, sequences and mapping types.
Organise applications using modules, packages and structured program design.
Read, write and process files and common data formats such as CSV, JSON and XML.
Use operating-system services and date/time functionality in Python programs.
Build database-connected Python applications.
Understand network programming and interaction with network services.
Create graphical interfaces for Python applications.
Develop multithreaded applications for suitable concurrent tasks.
Plan and execute unit tests for Python code.
Apply Python to data mining, data analysis and customisation projects.

SKILLS

Skills You Will Gain

Python programming
Advanced Python programming
Python data analysis
Data mining fundamentals
File and data-format processing
Database connectivity
Operating-system service integration
Network programming fundamentals
Module and package creation
Graphical user-interface development
Multithreading fundamentals
Unit testing and code quality practices

WHO SHOULD JOIN

Who Should Join?

The programme is suitable for students and working professionals who want to strengthen their Python programming and data-analysis capabilities at an intermediate level. It is relevant for learners moving from basic Python or another programming language towards more structured and advanced Python development.

PREREQUISITES

Prerequisites

Basic knowledge of programming is required. Familiarity with basic Python or another programming language will help learners progress comfortably through the advanced topics.

TRAINING APPROACH

Training Methodology

ACLM delivers the course through online instructor-led learning with one-to-one and group-training options. The programme combines approximately 40% conceptual instruction with 60% practical training, based on the supplied course outline. Learners receive notes, assignments and e-books, and practise concepts through guided exercises, coding tasks and practical projects.

CURRICULUM

Detailed Course Syllabus

Module	Topics / Lessons
Module 1: Advanced Python Foundations and Program Structure Refresh core Python concepts and establish the structured programming practices required for the rest of the course.	Course orientation and advanced Python learning pathway — Understand the course structure, practical expectations, project work and progression from core Python to advanced applications. 60 min Python refresher for intermediate learners — Review syntax, variables, operators, control flow, functions and common programming patterns. 120 min Data types and object-oriented thinking — Work with Python data types and understand how values, objects and operations behave in practical programs. 120 min Sequences and mapping types — Use strings, lists, tuples, sets and dictionaries for structured data storage and processing. 150 min Program structure and readable code — Organise code into logical components, use functions effectively and apply clear naming and documentation practices. 120 min Errors, exceptions and defensive programming — Identify common runtime problems, handle exceptions appropriately and make programs more reliable. 120 min Module 1 practical assignment — Build a small structured Python program using core data types, functions, collections and exception handling. 180 min
Module 2: Files, Data Formats and Reusable Components Develop practical skills for storing, retrieving and transforming information while creating reusable Python components.	File concepts and file operations — Read from and write to text files using safe and organised file-handling techniques. 120 min Working with CSV data — Process tabular CSV data, validate records and prepare information for analysis or reporting. 120 min Working with JSON data — Read, create and update JSON structures for configuration and data interchange tasks. 120 min Processing XML data — Understand XML structure and practise extracting and organising information from XML documents. 120 min Creating modules and packages — Separate application logic into reusable modules and organise related components into packages. 150 min Configuration and reusable utility design — Create configurable utilities that can be adapted for different inputs and practical customisation requirements. 120 min Module 2 practical assignment — Develop a data-conversion utility that reads one or more file formats, applies validation and produces an organised output. 180 min
Module 3: Operating-System Services and Date/Time Management Use Python to interact with operating-system services and manage dates and times in practical applications.	Python and operating-system services — Understand how Python programs can work with operating-system information and services. 120 min Paths, directories and environment interaction — Work with files, directories and environment-related information in a structured and portable manner. 120 min Process and command interaction concepts — Explore controlled interaction with system processes and commands, with attention to safe execution practices. 120 min Date and time objects — Create, compare and manipulate dates and times for application workflows. 120 min Formatting, parsing and time-based logic — Format dates, parse date strings and implement practical time-based conditions. 120 min Building command-oriented utilities — Combine system interaction, file handling and date/time logic in useful Python utilities. 120 min Module 3 practical assignment — Create a Python utility that organises files or records using operating-system services and date/time rules. 180 min
Module 4: Database Connectivity and Network Programming Connect Python applications with data stores and network services while maintaining clear separation between application and integration logic.	Database concepts for Python developers — Understand tables, records, queries and the role of database connectivity in Python applications. 120 min Connecting Python to a database — Establish a database connection, manage basic operations and handle connection-related issues. 150 min Queries and application data flow — Use Python to retrieve, insert and update data while organising the flow between application logic and the database. 150 min Database-connected application structure — Separate database operations into reusable components and design a maintainable application structure. 120 min Introduction to network programming — Understand network communication concepts relevant to Python applications and services. 120 min Interacting with network services — Practise the principles of sending requests, receiving responses and handling network-related failures. 150 min Module 4 practical assignment — Build a small Python application that stores and retrieves structured information and interacts with a network service concept. 210 min
Module 5: Graphical Interfaces, Multithreading and Testing Extend Python applications with user interfaces, concurrent task handling and systematic unit testing.	Graphical interface concepts — Understand the components and event-driven flow of graphical applications. 120 min Building a Python graphical interface — Create a simple interface with inputs, actions and displayed results for a practical application. 180 min Events and interface organisation — Connect user actions to application logic and organise interface code for maintainability. 120 min Multithreading fundamentals — Understand threads, concurrent execution and situations where multithreading may be useful. 150 min Creating multithreaded applications — Implement a controlled multithreaded task and consider shared data, coordination and reliability. 180 min Unit-testing principles — Define testable units, prepare test cases and verify expected Python behaviour. 150 min Implementing and running unit tests — Create and run unit tests, interpret failures and improve code based on test results. 180 min Module 5 practical assignment — Develop and test a small interface-driven application with a suitable multithreaded task or processing workflow. 240 min
Module 6: Data Analysis, Integration and Capstone Project Integrate the course skills in practical data mining, data analysis and customisation work, concluding with a guided capstone.	Python for data mining workflows — Plan a repeatable workflow for collecting, preparing, examining and organising data for practical use. 150 min Data preparation and quality checks — Clean structured data, identify inconsistencies and prepare reliable inputs for analysis. 150 min Data analysis with Python programming — Use Python logic to summarise data, compare values and generate meaningful outputs. 180 min Integrating files, modules and databases — Combine data sources and reusable components into a coherent Python solution. 180 min Customisation requirements and solution design — Translate a practical requirement into configurable components, processing steps and expected outputs. 150 min Capstone planning and implementation — Plan, develop and review a substantial project covering data mining, data analysis or customisation. 300 min Testing, documentation and presentation — Test the project, document its structure and present the implementation, results and learning outcomes. 180 min Final practical review — Review advanced Python concepts, resolve implementation gaps and consolidate the complete learning pathway. 120 min

HANDS-ON EXPERIENCE

Practical Projects

Data Mining Workflow — Create a Python-based workflow to load, clean, organise and inspect structured data. The project reinforces file handling, data processing, reusable modules and basic analytical reporting. Tools: Python, Python file handling, CSV and JSON processing, modules and packages
Python Data Analysis Report — Develop a practical data-analysis solution that prepares a dataset, performs structured analysis and presents findings in a clear output format. The project combines data handling, program structure and analytical reasoning. Tools: Python, data-processing techniques, CSV or JSON data, reusable functions and modules
Customisation and Utility Application — Build a configurable Python utility that accepts user-defined inputs, applies reusable processing logic and produces an organised result. Learners practise modular design, date/time handling, file operations and error-aware execution. Tools: Python, modules, packages, file handling, date/time management and unit testing
Database-Connected Python Application — Design a small Python application that connects to a database, performs basic data operations and separates database logic from the application structure. The project introduces practical database connectivity and maintainable code organisation. Tools: Python, database connectivity, modules and packages, structured program design
Concurrent Service Processing Task — Create a small application that processes independent tasks using multithreading and documents the design choices. Learners examine where concurrent execution can support practical Python workloads. Tools: Python, multithreading, functions, modules and testing practices

CAREER APPLICATION

Career Opportunities

The skills developed in this programme can support further learning and work in Python programming, data analysis, data-processing, automation, testing, database-connected applications and web-services development. Specific role suitability depends on the learner's prior education, experience, portfolio and assessment performance. ACLM does not represent this course as a guarantee of employment or placement.

CERTIFICATION

Certification

Learners who complete the applicable course requirements may receive an ACLM Certificate of Participation. The certification available for this programme is the ACLM Certificate of Participation.

FAQ

Frequently Asked Questions

What is the duration of the Advanced Python Training programme?

The course duration is six months.

Who is this course designed for?

It is designed for students and professionals with basic programming knowledge who want to develop intermediate-level Python and advanced Python skills.

Is the course available online?

Yes. The supplied course format is online, serving learners in India and international markets.

Is this a beginner-level Python course?

No. It is an intermediate-level programme. Basic programming knowledge is required, and familiarity with basic Python or another programming language is recommended.

What practical areas are covered?

The course covers data mining, data analysis, customisation, file and data-format processing, database connectivity, network programming, operating-system services, graphical interfaces, multithreading and unit testing.

What learning support is provided?

ACLM provides notes, assignments and e-books. Training is delivered through instructor-led, one-to-one and group-training approaches.

Will I receive a certificate?

Certification is available as an ACLM Certificate of Participation, subject to completion of the applicable course requirements.

Does the course guarantee a job or placement?

No. The course develops relevant skills and practical experience, but employment and placement outcomes depend on the learner's background, portfolio, performance and market conditions.

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