ACLM Institute of Professional Studies

Data Analysis Course

Data Analytics Course

05 MonthsOnline / OfflineIntermediateACLM CertificationACLM Certification

The ACLM Institute of Professional Studies Data Analysis Course is a 05-month intermediate programme delivered through Online / Offline training. It focuses on practical data analysis with Power BI and Python with Pandas. Learners work with data sources, Power Query, DAX, interactive dashboards, Python programming, data handling, statistical analysis, visualisation and report preparation. The course is designed for students and working professionals in India and international online markets.

COURSE OVERVIEW

Course Overview

WHY THIS COURSE

Why Learn This Course?

Data analysis helps organisations convert structured data into useful insights for review, reporting and decision-making. This course combines Power BI dashboard development with Python and Pandas-based analysis, enabling learners to work across data preparation, analysis, visualisation and reporting in a practical sequence.

LEARNING OUTCOMES

What You Will Learn

Use Power BI Desktop and Power BI Cloud for data analysis and reporting.
Import data from various data sources and prepare it with Power Query.
Create interactive dashboards with multi-level filters and slicers.
Apply DAX functions for calculated analysis and customised reporting.
Share live reports on Power BI online and export Power BI stories as a presentation deck.
Create user-focused and customisable Power BI reports.
Learn Python fundamentals, including operators, loops and statements.
Work with files, exceptions and data-handling tasks in Python.
Create functions, modules and classes.
Install, uninstall and update Python libraries.
Use Pandas DataFrames for statistical analysis and structured data work.
Create charts with Matplotlib and prepare a meaningful final report.

SKILLS

Skills You Will Gain

Programming fundamentals for data analysis
Power BI Desktop and Power BI Cloud usage
Data importing and preparation with Power Query
Dashboard design with filters and slicers
DAX-based calculations and analysis
Power BI report sharing and presentation export
Python file, exception and data handling
Python functions, modules and classes
Library installation and maintenance
Pandas DataFrame analysis
Statistical analysis of structured data
Matplotlib chart creation and report preparation

WHO SHOULD JOIN

Who Should Join?

Students and working professionals who want to develop practical skills in Power BI, Python and Pandas for data analysis.

PREREQUISITES

Prerequisites

Basic knowledge of programming is required. No additional prerequisite is specified.

TRAINING APPROACH

Training Methodology

Instructor-led Online / Offline training with an online one-to-one learning approach. The course includes ACLM notes, assignments and practical work based on Power BI, Python, Pandas and Matplotlib. Offline training is available in Geater Noida west, Greater Noida, Noida, Gaziabad and Delhi NCR. Online learning is available for learners in India and international markets. The course is not presented as a recorded programme.

CURRICULUM

Detailed Course Syllabus

Module	Topics / Lessons
Module 1: Foundations of Data Analysis and Power BI Workspace Establish the data-analysis workflow and become familiar with Power BI Desktop and Power BI Cloud. Learners begin by understanding how data moves from source to analysis, visualisation and report sharing.	Data Analysis Workflow and Reporting Objectives — Understand the stages of importing, preparing, analysing, visualising and reporting data. Translate a reporting requirement into a clear analysis objective. 90 min Power BI Desktop Orientation — Explore the Power BI Desktop environment, report-building workflow and core areas used for data preparation, modelling and visualisation. 120 min Power BI Cloud and Report Sharing Concepts — Understand the role of Power BI Cloud and the process of preparing reports for online sharing and review. 90 min Importing Data from Various Sources — Practise bringing data into Power BI from available sources and review the importance of consistent structure and usable fields. 120 min First Report Layout and Visual Selection — Create an initial report layout, select suitable visual forms and organise information for clear user interpretation. 120 min
Module 2: Power Query, DAX and Interactive Dashboards Develop practical Power BI reporting capability through data preparation, calculated analysis and interactive dashboard design.	Power Query Fundamentals — Use Power Query to inspect, prepare and transform imported data before it is used in a report. 120 min Data Cleaning and Preparation Workflow — Work through repeatable preparation steps and examine how clean, consistent data supports dependable analysis. 120 min DAX Fundamentals — Understand the purpose of DAX functions and use them to create calculated analytical outputs within Power BI. 150 min Unique DAX Functions for Analysis — Practise selected DAX functions for creating useful calculations and refining report-level analysis. 150 min Filters, Slicers and Multi-Level Interactivity — Build reports with multi-level filters and slicers so users can explore information according to their needs. 120 min Customisable Dashboard Design — Make a dashboard adaptable to user requirements through considered layout, navigation, visual organisation and interactive controls. 120 min
Module 3: Power BI Cloud Reporting and Presentation Complete the Power BI reporting cycle by reviewing report quality, sharing live reports online and presenting report stories effectively.	Report Review and Usability Checks — Review calculations, filters, slicers, visual consistency and the overall usability of a Power BI report. 90 min Publishing and Sharing Live Reports Online — Prepare reports for Power BI online and practise the workflow for sharing live reports with intended users. 120 min Power BI Stories and Export Workflow — Organise report insights into a coherent story and export Power BI stories as a presentation deck. 120 min Dashboard Refinement Assignment — Refine an assigned dashboard based on user requirements, improving customisation, interpretation and presentation quality. 150 min
Module 4: Python Programming for Data Analysis Build the Python foundation required for data handling and analytical work, progressing from core syntax to reusable program structures and library management.	Python Setup and Working Environment — Set up Python for course exercises and understand the basic workflow for writing and running Python code. 90 min Operators, Statements and Expressions — Use Python operators and statements to create clear, logical programs for analysis-related tasks. 120 min Loops and Repeated Data Tasks — Apply loops to process repeated operations and develop structured solutions to data-handling exercises. 120 min File Handling — Read, write and manage files for common data-handling workflows while maintaining an organised process. 120 min Exception Handling — Identify common execution problems and use exception handling to make Python programs more robust. 120 min Functions and Modules — Create reusable functions and modules to organise code and reduce repetition in analysis tasks. 150 min Classes and Basic Object-Oriented Structure — Create classes and understand how structured objects can support reusable Python solutions. 120 min Python Library Management — Install, uninstall and update Python libraries required for analytical work. 90 min
Module 5: Pandas, Statistical Analysis, Visualisation and Final Reporting Apply Python to structured data analysis with Pandas, create charts with Matplotlib and combine findings into a meaningful final report.	Pandas and DataFrames — Understand Pandas and use DataFrames as the primary structure for organising and analysing tabular data. 150 min Data Loading and DataFrame Handling — Load data into DataFrames and practise inspecting, selecting and working with structured data for analysis. 150 min Statistical Analysis with Pandas — Use Pandas to conduct statistical analysis, summarise data and interpret analytical outputs appropriately. 180 min Preparing Analysis Outputs — Organise analytical results into clear tables and outputs that can support visualisation and reporting. 120 min Chart Creation with Matplotlib — Create meaningful charts with Matplotlib and select visual forms that communicate analytical findings clearly. 150 min Interpretation and Meaningful Reporting — Connect statistical outputs and charts to a structured explanation, ensuring that the final report is understandable and relevant to its intended user. 150 min Integrated Final Project and Review — Complete an ACLM project combining data handling, analysis, visualisation and report preparation, followed by instructor-led review and assignment feedback. 180 min

HANDS-ON EXPERIENCE

Practical Projects

Power BI Interactive Dashboard Assignment — Import data from an available data source, prepare it with Power Query, create a multi-level dashboard with filters and slicers, add DAX-based calculations and customise the report for an intended user. Tools: Power BI Desktop, Power Query and DAX
Python Data Handling and Analysis Assignment — Use Python to work with files, handle exceptions, apply operators, loops and statements, and organise analysis through functions and modules. Tools: Python
Pandas Statistical Analysis Project — Load structured data into Pandas DataFrames, carry out statistical analysis, examine the results and prepare analysis outputs suitable for reporting. Tools: Python and Pandas
Matplotlib Visualisation and Final Report — Create meaningful charts from analysed data with Matplotlib and compile the findings into a structured report. Tools: Python, Pandas and Matplotlib
Integrated Data Analysis Project — Complete an end-to-end assignment that combines data importing or file handling, preparation, analysis, visualisation and presentation through a Power BI report or Python-based report workflow. Tools: Power BI, Power Query, DAX, Python, Pandas and Matplotlib

CAREER APPLICATION

Career Opportunities

The skills developed in this course can support practical work in data preparation, dashboard reporting, business reporting, Python-based data handling and analytical visualisation. Learners can apply these capabilities in academic, project-based and professional reporting environments, depending on their experience and organisational requirements.

CERTIFICATION

Certification

Learners who complete the programme receive an ACLM certificate of participation. Certification availability is subject to the course arrangement and completion requirements communicated by ACLM Institute of Professional Studies.

FAQ

Frequently Asked Questions

What is the duration of the ACLM Data Analysis Course?

The course duration is 05 Months.

What topics are covered in the course?

The course covers analysis with Power BI, Power BI Desktop and Cloud, Power Query, DAX, dashboards, filters, slicers, live report sharing, Python programming, file and exception handling, functions, modules, classes, library management, Pandas, statistical analysis, Matplotlib and final report preparation.

Is this course suitable for beginners?

The course level is Intermediate and basic knowledge of programming is required. Python fundamentals are included, but learners should be comfortable with basic programming concepts before starting.

Who can join this course?

The course is intended for students and working professionals.

What training modes are available?

ACLM offers Online / Offline training. The methodology is instructor-led with an online one-to-one learning approach.

Where is offline training available?

Offline training is available in Geater Noida west, Greater Noida, Noida, Gaziabad and Delhi NCR.

Is the course available online outside India?

Yes. Online learning is available for India and international markets.

Are recorded classes included?

The supplied course details specify that the course is not recorded. Training is delivered through the stated instructor-led formats.

Does the course include practical work?

Yes. The course includes projects and assignments by ACLM, supported by ACLM notes and practical exercises across Power BI, Python, Pandas and Matplotlib.

What certificate is provided?

ACLM Institute of Professional Studies provides an ACLM certificate of participation, subject to the applicable course completion requirements.

What software and technologies are used?

The course uses Power BI Desktop, Power BI Cloud, Power Query, DAX, Python, Pandas and Matplotlib.

START YOUR JOURNEY

Ready to Start Learning?

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