LIMITED TIME OFFER25% off on ACLM & University CoursesEnds in --:--:--
Home › Courses › Online Python Training
ACLM Institute of Professional Studies

Online Python Training

Online Python Training

06 MonthsOnline / OfflineIntermediateACLM CertificationACLM Certification
Explore Course
The Online Python Training is to perfect yourself in Python. Python is in huge demand by the top technocrat companies. As a booster dose to your programming skill, ACLM since 2016, organised more than 100+ workshops in various colleges / universities and corporate institutions to make awareness into Data Analytics and Data Science through python.
COURSE OVERVIEW

Course Overview

Online Python Training by ACLM Institute of Professional Studies is a six-month, intermediate-level programme designed for students and professionals with basic programming knowledge. The course develops practical capability in Python Core, advanced Python, exception handling, looping constructs, data structures, file handling, NumPy, Pandas, SQL, Python-SQL integration, predefined structured algorithms, data interpretation and project development. Training is available in Online / Offline modes, with instructor-led online one-to-one learning, notes, assignments and ebooks. Offline training is available in Greater Noida West, Greater Noida, Noida, Ghaziabad and Delhi NCR. Online learners may join from India and international markets.

WHY THIS COURSE

Why Learn This Course?

Python is a versatile programming language used for application development, automation, data handling and analysis. This ACLM programme combines Python programming with SQL-based data analysis, structured algorithms and practical projects so that learners can build a stronger foundation for Python-based project work. The six-month structure provides time for progressive learning, assignments, assessments and guided practice.

LEARNING OUTCOMES

What You Will Learn

  • Python syntax, variables, data types, operators and program structure
  • Conditional statements and looping constructs
  • Functions, modules, packages and reusable Python code
  • Exception handling and practical error management
  • Classes, objects and object-oriented programming concepts
  • Python data structures and their practical use
  • File handling and application-oriented file operations
  • Working with PyCharm as a Python development environment
  • NumPy fundamentals for numerical and structured data operations
  • Pandas fundamentals for tabular data handling and analysis
  • SQL concepts required for data interpretation
  • Python-SQL connectivity and database-oriented workflows
  • Predefined structured algorithms in Python
  • Planning, developing and presenting Python-based projects
  • Assignment completion, assessments and preparation for the ACLM Certificate of Participation
SKILLS

Skills You Will Gain

  • Write structured Python programs using core and advanced language features
  • Apply conditions, loops, functions and exception handling to solve programming tasks
  • Design classes and objects for organised, reusable Python applications
  • Select and use appropriate Python data structures
  • Read, write and process files using Python
  • Use PyCharm for Python development and project organisation
  • Perform numerical operations with NumPy
  • Clean, transform and interpret tabular data with Pandas
  • Use SQL for data interpretation and analysis tasks
  • Connect Python workflows with SQL-based data handling
  • Implement predefined structured algorithms in Python
  • Develop Python projects involving data analysis and SQL data analysis
  • Complete technical assignments and demonstrate learning through assessments
WHO SHOULD JOIN

Who Should Join?

Students and professionals who want to strengthen their Python programming, data analysis and SQL data analysis skills through a structured six-month programme.

PREREQUISITES

Prerequisites

Basic Programming Knowledge.

TRAINING APPROACH

Training Methodology

The programme uses instructor-led training with online one-to-one learning support. Learning is supported by notes, assignments and ebooks, followed by practical exercises, project work and assessments. Training is available in Online / Offline modes. Offline delivery is available in Greater Noida West, Greater Noida, Noida, Ghaziabad and Delhi NCR. Online participation is available for learners in India and international markets.

CURRICULUM

Detailed Course Syllabus

ModuleTopics / Lessons
Python Development Foundations
Establish a dependable working foundation in Python and the PyCharm development environment before progressing to advanced programming and data-focused topics.
  • Course Orientation and Python Environment — Understand the course structure, project expectations and assessment approach. Set up and navigate PyCharm for Python development. 90 min
  • Python Syntax, Variables and Data Types — Learn Python program structure, naming, variables, common data types, type conversion and basic input and output. 120 min
  • Operators and Expressions — Work with arithmetic, comparison, logical and assignment operators to build clear Python expressions. 90 min
  • Conditional Programming — Use if, elif and else statements to implement decision-making logic and validate program conditions. 120 min
Looping Constructs, Functions and Core Programming
Build reusable programs using loops, functions and modular programming techniques, with practical exercises for structured problem solving.
  • Looping Constructs — Apply for and while loops, nested loops, loop control statements and iteration patterns to solve repetitive tasks. 120 min
  • Functions and Parameters — Create functions using parameters, return values, default arguments and suitable naming and organisation practices. 120 min
  • Modules, Packages and Code Reuse — Organise Python code into modules and packages and understand how reusable components support maintainable applications. 90 min
  • Core Programming Assignment — Complete an instructor-guided programming assignment combining conditions, loops, functions and input handling. 120 min
Exception Handling and File Handling
Develop more reliable Python applications by managing runtime errors and working with files for practical application usage.
  • Understanding Python Exceptions — Identify common runtime errors and understand the role of exceptions in application execution. 90 min
  • Exception Handling Techniques — Use try, except, else and finally appropriately, including handling multiple exception conditions and meaningful error messages. 120 min
  • File Input and Output — Read from and write to files, manage file modes and organise file-based application workflows. 120 min
  • File Handling Application Exercise — Build a small file-oriented application that combines file operations, validation and exception handling. 120 min
Classes, Objects and Data Structures
Learn object-oriented programming concepts and select suitable built-in data structures for Python application development.
  • Classes and Objects — Define classes, create objects and understand attributes, methods and object-level behaviour. 120 min
  • Object-Oriented Programming Practices — Work with constructors, method design and basic inheritance concepts to organise application logic. 120 min
  • Python Data Structures — Use lists, tuples, sets and dictionaries and compare their practical use in different programming situations. 150 min
  • Data Structures Assignment — Solve programming tasks that require selecting, combining and processing appropriate Python data structures. 120 min
Advanced Python Programming
Extend programming capability through more advanced language usage, structured code design and algorithmic thinking.
  • Advanced Python Programming Patterns — Practise concise, reusable and organised Python code using advanced programming techniques relevant to application development. 120 min
  • Structured Algorithm Design — Break problems into logical steps, define inputs and outputs and translate solution plans into Python implementations. 120 min
  • Predefined Structured Algorithms — Study and implement predefined structured algorithms in Python through guided coding exercises. 150 min
  • Advanced Python Practice Assignment — Complete a multi-part assignment that applies advanced Python concepts and structured algorithmic thinking. 120 min
PyCharm and Project Organisation
Use PyCharm effectively while developing, testing and organising Python projects and their supporting files.
  • PyCharm Project Workflow — Create projects, manage files, organise source code and use the development workspace efficiently. 90 min
  • Running and Testing Python Programs — Execute programs, inspect outputs, identify issues and refine code through repeated testing. 120 min
  • Organising a Python Project — Structure application files, supporting resources and documentation for a clear and manageable project. 90 min
  • Project Planning Workshop — Convert a project requirement into objectives, data needs, processing steps, outputs and an implementation plan. 120 min
NumPy for Numerical Data
Introduce NumPy as a practical Python library for numerical data organisation, processing and analysis.
  • NumPy Arrays and Data Organisation — Create and inspect arrays and understand how numerical data can be represented for processing. 120 min
  • Array Operations and Calculations — Perform common array operations, calculations and transformations using NumPy. 150 min
  • Working with Structured Numerical Data — Apply NumPy techniques to organise and process structured numerical information. 120 min
  • NumPy Practical Assignment — Develop a numerical data-processing task and document the inputs, operations and results. 120 min
Pandas for Data Analysis
Use Pandas to work with tabular data and develop a practical workflow for data inspection, transformation and interpretation.
  • Pandas Data Structures — Understand the purpose and use of Series and DataFrame structures for tabular data handling. 120 min
  • Loading and Inspecting Data — Load data into Pandas, inspect its structure and identify fields, values and basic data-quality considerations. 120 min
  • Filtering, Transformation and Aggregation — Filter records, transform columns and perform grouped or aggregated analysis using Pandas. 150 min
  • Pandas Analysis Project Exercise — Complete a guided analysis workflow and communicate the key observations obtained from the data. 150 min
SQL and Data Interpretation
Build the SQL knowledge required to interpret structured data and connect database-oriented analysis with Python workflows.
  • SQL Foundations for Data Work — Understand tables, fields, records and the role of SQL in structured data interpretation. 90 min
  • Querying and Filtering Data — Write queries to select, filter and sort data for analysis tasks. 120 min
  • Data Interpretation with SQL — Use SQL results to examine patterns, compare records and answer defined data questions. 120 min
  • SQL Analysis Assignment — Complete an assignment involving structured queries and interpretation of the resulting data. 120 min
Python SQL Integration
Combine Python programming and SQL data handling to create practical workflows for data analysis projects.
  • Python-SQL Workflow Concepts — Plan the stages of a Python and SQL workflow, including data access, processing and output requirements. 90 min
  • Working with SQL Data through Python — Apply Python-based handling of SQL-oriented data for analysis and application use cases. 150 min
  • Combining Python, Pandas and SQL Analysis — Develop a workflow that uses Python and Pandas to process and interpret data obtained through SQL-oriented operations. 150 min
  • Python SQL Mini Project — Build and document a small project that demonstrates Python and SQL data analysis together. 180 min
Integrated Project Development
Apply the complete learning sequence to a substantial Python project involving programming, data handling, analysis or SQL data analysis.
  • Project Requirement and Scope Definition — Define the project problem, intended users or use case, inputs, outputs, technologies and completion criteria. 120 min
  • Project Implementation Sprint — Implement the planned Python project with structured code, suitable data structures and relevant libraries or SQL workflows. 240 min
  • Testing, Error Handling and Refinement — Test the project, manage identified errors, improve clarity and refine the output based on review. 180 min
  • Project Documentation — Prepare project notes covering purpose, setup, processing steps, key code decisions and results. 120 min
Assignments, Assessments and Course Completion
Consolidate learning through review, practical assignments, assessments and project presentation.
  • Topic-Wise Revision and Doubt Resolution — Review core concepts across Python, data structures, NumPy, Pandas and SQL, with focused clarification of difficult areas. 120 min
  • Practical Assessment — Demonstrate the ability to apply Python programming and data analysis concepts to defined practical tasks. 180 min
  • Project Presentation and Evaluation — Present the completed Python project, explain the workflow and respond to technical review questions. 150 min
  • Course Review and Certification Process — Review learning outcomes, discuss next steps for continued practice and complete the applicable ACLM course completion process. 90 min
HANDS-ON EXPERIENCE

Practical Projects

  • Python Core Programming Project — Develop a structured Python application using variables, data types, conditional logic, looping constructs, functions and appropriate data structures. The project should include input handling, validation and clearly organised source code. Tools: Python, PyCharm
  • File Handling and Exception Management Application — Build a Python application that reads, writes and processes files while managing invalid inputs and operational errors through appropriate exception handling. Learners document the expected inputs, outputs and error cases. Tools: Python, PyCharm, text or structured data files
  • NumPy Data Processing Project — Create a numerical data-processing workflow using NumPy arrays and operations. The project focuses on organising data, performing calculations and presenting meaningful processed results. Tools: Python, NumPy, PyCharm
  • Pandas Data Analysis Project — Work with a tabular dataset using Pandas. The project includes loading data, inspecting its structure, applying transformations, performing analysis and communicating the resulting observations. Tools: Python, Pandas, PyCharm
  • Python and SQL Data Analysis Project — Develop a project that combines Python processing with SQL-based data interpretation. Learners design a practical workflow for querying, handling and analysing structured data, then present the results with supporting documentation. Tools: Python, SQL, Python-SQL integration, PyCharm
CAREER APPLICATION

Career Opportunities

The skills developed in this course can support Python-based project work involving programming, data handling, data analysis and SQL data analysis. Learners may use the knowledge gained as a foundation for further development in Python programming and related technical roles, subject to their individual experience, portfolio and employer requirements. ACLM does not make a placement, employment or salary guarantee through this course.

CERTIFICATION

Certification

Learners who complete the applicable course requirements can receive the ACLM Certificate of Participation. Certification availability is subject to ACLM's course completion and assessment process.

FAQ

Frequently Asked Questions

What is the duration of the Online Python Training programme?

The programme duration is 06 Months.

Who can join this Python course?

The course is intended for students and professionals with basic programming knowledge.

What are the prerequisites?

Basic Programming Knowledge is required.

Is the course available online and offline?

Yes. Training is available in Online / Offline modes. Offline training is available in Greater Noida West, Greater Noida, Noida, Ghaziabad and Delhi NCR.

Can learners outside India join online?

Yes. The online market includes India + International.

What Python topics are covered?

The course covers Python Core, Python Advanced, looping constructs, exception handling, classes, objects, data structures, file handling, PyCharm, NumPy, Pandas, structured algorithms and project development.

Does the course include SQL?

Yes. It includes data interpretation with SQL, Python SQL and Python-based project work involving SQL data analysis.

Are practical projects included?

Yes. The programme includes Python projects on various topics, assignments and integrated projects involving Python, data analysis and SQL data analysis.

What learning materials are provided?

The training methodology includes notes, assignments and ebooks.

Is certification available?

Yes. The stated certification is the ACLM Certificate of Participation, subject to the applicable course completion and assessment process.

Is the course recorded?

No. The course facts specify that the programme is not recorded.

START YOUR JOURNEY

Ready to Start Learning?

Contact ACLM Institute of Professional Studies for course guidance, demo scheduling and registration.

Contact ACLM

Want the complete syllabus?

Get the detailed module-wise ACLM syllabus in PDF after mobile verification.

Register Now