Overview
The Certified Professional Diploma in Data Analytics is a comprehensive training program offered by ICIT Computer Institute, an institute established in 2000 with a strong focus on computer education and skill development.
This course is designed with a strong emphasis on practical, industry-oriented learning, following a structured 20% theory and 80% hands-on practical approach. Students are trained through an extensive mix of assignments, corporate projects, case studies, and real-world industry exposure. As part of the curriculum, learners work on 50+ case studies and more than 50 projects, helping them build strong analytical and problem-solving skills relevant to the data industry.
The program also highlights several key features, such as small batch sizes for better learning outcomes, personalised attention through a “One Student One Computer” policy, and access to detailed study materials along with additional practice sessions. Alongside technical training, students are also given industry orientation to understand real business environments.
Finally, the diploma includes comprehensive placement assistance, preparing students for career opportunities in roles such as Data Analyst, Business Analyst, and Data Scientist, and guiding them from training to professional employment.
Course Curriculum
The curriculum is divided into five core modules:
1. Advanced Excel
Data Management & Formatting: Filtering databases, sorting data, advanced formatting (conditional formatting for rows, columns, and cells), and data validation.
Functions & Formulas: Extensive use of logical functions (IF, AND, OR, NOT), date/time functions, COUNTIF, SUMIF, and lookup functions including VLOOKUP, HLOOKUP, XLOOKUP, and nested dynamic variations.
Analysis & Reporting: Pivot Tables, Pivot Charts, Slicers, What-if analysis, Goal Seek, Scenario Manager, and Multiple Level Subtotal Reports.
Automation: Introduction to VBA, along with macro definitions, recording, running, and storing.
2. Management Information Systems (MIS)
Fundamentals: Types and sources of data, data collection, storage, data quality, cleaning, and data warehousing.
Analysis Techniques: Descriptive statistics, inferential statistics, and data visualization.
Tools & Applications: Using Excel, Power BI, and Tableau for business decision-making, customer behavior analysis, and financial forecasting.
Advanced Concepts: Introductory concepts in machine learning, deep learning, and big data analysis.
3. Power BI
Power Query: Extract, Transform, and Load (ETL) processes, datatypes, filters, inbuilt column/row transformations, and merging/appending queries.
Power Pivot & DAX: Data modeling, relationships, and enhancing data models using DAX (Data Analysis Expressions) including Date/Time, Text, Logical, Math, Statistical, and Filter functions.
Power View & Service: Creating visual reports (trend data, KPIs), drill-down capabilities, dashboard development, setting up data gateways, and implementing row-level security.
4. SQL Curriculum
The SQL module focuses on Oracle Database 12c, covering everything from fundamental queries to advanced database management and security.
Database Basics & Data Retrieval:
Introduction to Oracle Database 12c features, physical aspects, and using the SQL Developer environment.
Retrieving data using the SELECT statement and applying arithmetic operators.
Restricting and sorting data using the WHERE clause, logical/comparison operators, and ORDER BY.
Functions & Data Aggregation:
Using single-row functions for string, number (ROUND, TRUNC), and date manipulation.
Implementing conversion functions (TO_CHAR, TO_NUMBER, TO_DATE) and conditional expressions (NVL, COALESCE, IF THEN ELSE).
Aggregating data using Group functions, organizing output with GROUP BY, and filtering groups with HAVING.
Advanced Querying:
Displaying data from multiple tables using Joins.
Solving complex analytical problems using various Subqueries (single-row, multiple-row, multiple-column, correlated, scalar) and utilizing the WITH clause.
Combining results from multiple queries using SET operators.
Data Manipulation & Definition (DML & DDL):
Managing records with DML statements (INSERT, UPDATE, DELETE) and handling transaction states with COMMIT and ROLLBACK.
Structuring tables using DDL statements, managing data types, and defining constraints during table creation.
Manipulating large datasets through multi-table inserts, subquery targeting, and merging rows.
Schema Objects & Security:
Creating and maintaining other schema objects, such as views, sequences, indexes, and synonyms.
Modifying table structures (adding/dropping columns) and managing constraints.
Controlling user access by creating users, granting/revoking system and object privileges, and assigning roles.
Querying Data Dictionary Views to inspect table, constraint, and index information.
Advanced Tools:
Implementing Oracle Data Pump to query External Tables.
Using Regular Expression functions (REGEXP_LIKE, REGEXP_REPLACE, REGEXP_COUNT) to search and extract complex patterns.
5. Python Curriculum
The Python module is comprehensive, starting with foundational programming logic and progressing into application development, database integration, and multi-threading.
Python Basics & Environment:
Introduction to the Python language, installation, using the Python Interpreter, and setting up IDEs.
Fundamentals of variables, keywords, data types, static vs. dynamic typing, and various operators (arithmetic, logical, bitwise, membership, identity).
Control Flow & Functions:
Controlling program logic with if-elif-else statements, while loops, nested for-in loops, and control statements like break, continue, and pass.
Defining functions, handling parameters (call by value/reference), managing variable scope (local/global), implementing recursion, and writing anonymous (lambda) functions.
Core Data Structures:
Strings: Access, escape sequences, formatting, and string methods.
Lists: Creation, comprehension, matrix operations, and implementing stacks and queues.
Tuples, Sets, and Dictionaries: Exploring immutability, comprehensions, and specific methods and operations for each structure.
Modules, Packages & File Handling:
Creating, importing, and reloading modules and packages (including installing third-party tools), and navigating namespaces.
File operations including opening/closing modes, reading, writing, appending, handling binary files, and serialization with the pickle module.
Object-Oriented Programming (OOP) & Exceptions:
Mastering OOP concepts: Defining classes, instantiating objects, handling constructors, instance vs. class attributes, private methods, inheritance, and method overloading/overriding.
Exception handling techniques using try, catch (detecting multiple exceptions), finally blocks, and creating user-defined exceptions.
Advanced Programming & Architecture:
Multi-Threading: Understanding process vs. thread multitasking, creating threads, synchronization, implementing locks, inter-thread communication, and managing daemon threads.
GUI & Event Handling: Building graphical interfaces using Tkinter (creating windows, labels, buttons, frames, menus) and binding mouse/keyboard events.
Database Integration: Using MySQL.connector to connect to a database, create tables, and execute SQL operations directly from Python.
Deployment: Converting Python scripts into deployable executable files.
Live Projects:
Who should attend?
Students interested in industry careers such as:
Data Analyst
Business Analyst
Data Scientist
Market Research Analyst
FAQ's
Q: What modules are covered in the Data Analytics course?
A: The course covers Advanced Excel, Management Information Systems (MIS), Power BI, SQL, and Python.
Q: What career opportunities can I pursue after completing this course?
A: The course prepares you for roles such as Data Analyst, Business Analyst, Data Scientist, and Market Research Analyst.
Q: Does the institute offer help with getting a job?
A: Yes, the institute offers "Complete Placement Assistance" alongside interview preparation.
Q: What is the training methodology like? Is it mostly theoretical?
A: The training is highly practical, structured as 20% Theory and 80% Practicals. The learning involves hands-on assignments, corporate projects, case studies, and industry orientation.
Q: Is the ICIT Computer Institute certified or recognised?
A: Yes, ICIT is an ISO 9001:2015 Certified Company and is recognised by the government (???? ?????????? ??????). It is also recognised by NIELIT and is a Vocational Training Provider (VTP) centre of the Maharashtra State Skill Development Society (MSSDS).
Q: Do I get a certificate at the end of the course?
A: Yes, upon completion, students earn a "Certified Professional Diploma in DATA ANALYTICS".