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Data Analyst / Data Analysis / Data Analytics
Course Syllabus :-
Data Analyst / Data Analysis / Data Analytics Course Details
Tools Covered: Excel → SQL → Python (Pandas + Matplotlib) → Power BI → Tableau
Excel — Beginner to Advanced
SQL — Beginner to Advanced
Python (Pandas + Matplotlib) — Beginner to Advanced
Power BI — Beginner to Advanced
Tableau — Beginner to Advanced
1. Excel — Beginner to Advanced
Beginner:
- Introduction to Excel interface, ribbon, workbooks, worksheets
- Basic formulas: SUM, AVERAGE, COUNT, MIN, MAX, IF
- Sorting, filtering, conditional formatting
- Basic charts: bar, line, pie
- Introduction to Pivot Tables
Intermediate:
- Advanced formulas: VLOOKUP, HLOOKUP, INDEX-MATCH
- Data cleaning techniques: remove duplicates, text functions, data validation
- Advanced Pivot Tables, slicers, and pivot charts
- Introduction to Excel dashboards
Advanced:
- Dynamic dashboards with interactive controls
- Power Query for data import and transformation
- Macros for automation (basic)
- What-if analysis: scenarios, goal seek, data tables
- Advanced charting: combo charts, waterfall charts
Practical:
- Build a Sales Dashboard with Pivot Tables, charts, and slicers
- Perform data cleaning on a messy dataset
2️. SQL — Beginner to Advanced
Beginner:
- Introduction to databases and tables
- SELECT, WHERE, ORDER BY
- Aggregate functions: SUM, AVG, COUNT, MIN, MAX
- Basic filtering and sorting
Intermediate:
- JOINs: INNER, LEFT, RIGHT, FULL
- Subqueries and nested queries
- GROUP BY and HAVING clauses
- Handling NULLs and data types
Advanced:
- Views, temporary tables, and indexes
- Window functions: ROW_NUMBER, RANK, LEAD, LAG
- Complex queries combining multiple tables
- Query optimization basics
Practical:
- Extract insights from Sales or Customer database using JOINs, subqueries, and aggregates
- Generate a report showing total sales by region and top-selling products
3️. Python (Pandas + Matplotlib) — Beginner to Advanced
Beginner:
- Python basics: variables, data types, loops, functions
- Introduction to Pandas: Series, DataFrame
- Loading datasets: CSV, Excel
- Basic operations: head(), tail(), info(), describe()
Intermediate:
- Data cleaning: handling missing values, duplicates
- Filtering, grouping, aggregating data
- Merging and joining DataFrames
- Introduction to Matplotlib: line, bar, pie, scatter plots
Advanced:
- Advanced Pandas operations: pivot tables, multi-indexing, time series
- Advanced Matplotlib visualizations and styling
- Combining Pandas and Matplotlib for dashboards
- Exporting processed data to CSV/Excel for reporting
Practical:
- Clean, analyze, and visualize a dataset of sales or customer data
- Create trend analysis charts and summary statistics
4. Power BI — Beginner to Advanced
Beginner:
- Introduction to Power BI Desktop and service
- Connecting to data sources (Excel, CSV, SQL)
- Basic visualizations: bar, column, pie charts
- Filters and slicers
Intermediate:
- Data modeling and relationships
- Calculated columns and measures using DAX
- Advanced visualizations: combo charts, KPI, cards
- Power BI Service: dashboards and sharing
Advanced:
- Advanced DAX formulas
- Row-level security, bookmarks, and interactivity
- Power Query transformations
- Optimizing reports for performance and accessibility
Practical:
- Build a Sales Performance Dashboard with multiple charts, slicers, and KPIs
5️. Tableau — Beginner to Advanced
Beginner:
- Tableau interface, connecting to data sources
- Basic charts: bar, line, pie
- Filters, sorting, and grouping
- Creating simple dashboards
Intermediate:
- Calculated fields, sets, and parameters
- Advanced charts: dual-axis, heatmaps, tree maps
- Dashboard design best practices
- Basic storytelling with Tableau
Advanced:
- LOD (Level of Detail) expressions
- Advanced interactivity with actions and filters
- Combining multiple data sources
- Optimizing dashboards for performance
Practical:
- Build an interactive Tableau dashboard for a real-world dataset
- Use calculated fields and filters for deeper insights
Capstone Project Ideas
- Build a full Sales Analysis workflow: Excel data cleaning → SQL queries → Python analysis → Power BI/Tableau dashboard
- Customer segmentation and visualization
- Marketing campaign analysis with insights and charts
Enquiry Form (Call @ Chandmari Centre-7670046464 / Adabari Centre-9864093327)
Python Programming
Course Syllabus :-
Introduction to Python interpreter/shell, indentation, identifiers and keywords (arithmetic operator, relational operator, Bool operator and bitwise operator) and expr Unit
Create python program, input and output statements, defining functions, control state , loop control statements, break, continue and pass, exit function default argument and exceptions.
Strings and Lists: String class, built-in functions for string, string traversal, string operators and operations, Lists creation, traversal, slicing and splitting operations, passing list to a function
Object Oriented Programming: Introduction to Classes, Objects and Methods, Standard Libraries, File handling through libraries.
JAVA Programming
Course Syllabus :-
JAVA language basics Basic features, Java virtual machine concepts creation of JAVA, executing a java program using command line arguments The primitive data types and Variables, Java Key words, integer and floating point data type, character and Boolean types, declaring and initialization variables, Type conversion and casting
Operators and Control Statements Java operators – Arithmetic operators, Bitwise operators, Relational operators, Boolean logical operators, Assignment operator, Conditional operator, if and switch statements, iteration statements, jump statements.
Classes and Methods Class fundamentals, Objects, Constructors, this keyword, finalize () method Overloading methods, garbage collection, Returning objects, introducing access control, understanding static, introducing final, introducing nested and inner classes
Strings String operations, Character Extraction, Comparing, Searching & Modifying the strings, Data conversion using valueOf(), String Buffer
Inheritance basics, using super, creating a multilevel hierarchy, method overriding, dynamic method dispatch, using abstract classes, using final with inheritance
Packages and interfaces Packages, access protection ,importing packages, interfaces
Multithread programming The JAVA thread model, creating a thread, creating a multiple thread, Using is Alive() and join (), Interthread communication, suspending, resuming and stopping threads, using multithreading.
Exception handling Exception handling fundamentals, exception types, uncaught exceptions, using try and catch.
Enquiry Form (Call @ Chandmari-7670046464 / Adabari-9864093327)
C Programming
Course Syllabus :-
Overview of C , Importance of C, C program structure, executing C program. Variables, Data Types, Constants: integer constant, real constant, character constant, string constant, Character set, C tokens, keywords and identifiers, variables declaration, Assigning values to variables—Assignment statement, declaring a variable as constant, as volatile.
Operators and Expression Categories of operator- Arithmetic, Relational, logical, assignment, increment, decrement, conditional, bitwise and special operators; arithmetic expressions, precedence and associativity of operators, type conversions, mathematical functions.
Decision Making and Branching Statement if statement, statement, nested statement , statement, go to statement.
Decision Making and Looping Definition of loop, categories of loops, for loop while loop, do-while loop, break statement, continue statement.
Arrays Declaration and accessing of one & two-dimensional arrays, initializing two-dimensional arrays, multidimensional arrays.
Functions The form of C functions, Return values and types, return statement, calling a function, categories of functions, Nested functions, Recursion, functions with arrays, call by value, call by reference , storage classes.
Structures and Unions Defining, giving values to members, initialization and comparison of structure variables, array of structure, array within structure, structure within structure, structures and functions, unions.
Pointers Definition of pointer, declaring and initializing pointers, accessing a variable through address and through pointer, pointer expressions, pointer increments and scale factor, pointers and arrays, pointers and functions, pointers and structures.
File Management in C Opening, closing and I/O operations on files, random access to files, command line arguments.
C++ Programming
Course Syllabus :-
Principles of OOP
What is OOP, Difference between OOP and Structured Programming, Basic Concepts of Class, Object, Data abstraction and Encapsulation, Inheritance , Polymorphism, Dynamic binding, Message passing, Benefits of OOP, OOP languages, Applications
Introduction to C++
Features of C++ , Structure of a C++ Program, The iostream file, cin and cout object, Saving a C++ program, Compiling and Running a C++ Program.
Variables, Constants, Operators and Expressions and Control Statements (if, switch, for, while, do-while) in C++.
Functions in C++
Return types in main(), function prototyping, Call by reference, Call by value, Call by address.
Inline functions, Default arguments, Constant argument, Function overloading.
Classes and Object:
Specifying a class, Member of a class, Access specifier , Use of scope resolution operator(::) , Creating object, Accessing class members, Defining member functions, Friend function, Friend class, Object as function arguments, Constructor , Constructor overloading, Default argument constructor, Copy constructor, Parameterized constructor, Default constructor, Destructors.
Data Structures
Course Syllabus :-
Concept of Data Types, elementary structure, words and their interpretations, packed words Arrays: Types, memory representation, address translation functions for one & two dimensional arrays, different examples.
Linked Structure: Singly and doubly linked list, circular and non circular, list manipulation with pointers, example involving insertion and deletion of elements and their comparative studies with implementations using array structure Stacks and Queues Definitions, representation using array and linked list structure, application of stack and queues in simulation, postfix conversion and evolution of arithmetic expressions
Binary Trees: Definition, quantitative properties, memory representation, Trees traversal algorithms (recursive and non-recursive), threaded trees, BFS, DFS
Searching Linear and binary search algorithms, performance and complexity, binary search trees (construction, insertion, deletion and search), Concept of optimal binary search trees.
Sorting: Terminology, performance evaluation, sorting algorithms (non recursive, recursive description, Complexity, advantages and disadvantage, implementation) Bubble sort, insertion sort, selection sort, Tree sort, heap sort, quick sort, merge sort & radix sort. External Sorting.
Analysis of Algorithm Time and Space complexity of algorithms, average case and worst case analysis, asymptotic notation as a measure of algorithm complexity, O and notations. Analysis of sorting algorithms- Selection sort, Bubble sort, Insertion sort, Heap sort, Quick sort and analysis of searching algorithms linear search and binary search
Enquiry Form (Call @ Chandmari-7670046464 / Adabari-9864093327)
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