SikshaSarovar is a free e-learning platform offering structured programming courses and complete university subject coverage for students across India. Learn at your own pace with clear lessons, code examples, and practical exercises — no login required for most content.
Our platform serves students preparing for university exams, competitive programming, and professional development. We cover programming fundamentals through advanced topics in Artificial Intelligence, Machine Learning, and Data Science.
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Beginner
Master C and C++ from the ground up. Covers variables, data types, operators, control flow, functions, arrays, pointers, structures, object-oriented programming (OOP), and file handling.
- Introduction to C programming language
- Variables, data types, and operators
- Control structures: if/else, loops, switch
- Functions, recursion, and arrays
- Pointers and memory management
- Structures, unions, and enumerations
- Object-Oriented Programming in C++
- File handling and stream I/O
Beginner
Complete HTML course from first principles. Learn how browsers work, semantic markup, forms, tables, accessibility and modern HTML5 features used in real web projects.
- Web concepts, browsers, and HTTP basics
- HTML document structure and head elements
- Text, headings, paragraphs, and formatting tags
- Links, images, and multimedia
- Lists: ordered, unordered, and description lists
- Tables: structure, merging cells, styling
- Forms: inputs, labels, validation, submission
- Semantic HTML5: article, section, nav, footer
Beginner
From basic CSS selectors to modern layouts. Learn the box model, Flexbox, CSS Grid, responsive design, transitions, animations and best practices for scalable stylesheets.
- Selectors, specificity, and cascade rules
- Box model: margin, padding, border
- Display types and positioning
- Flexbox layout system
- CSS Grid for complex layouts
- Responsive design and media queries
- Transitions and CSS animations
- CSS variables and custom properties
Intermediate
Server-side web development with PHP. From basic syntax to working with MySQL databases, handling forms, managing sessions and building dynamic web applications.
- PHP syntax, variables, and data types
- Control structures and functions
- Arrays, strings, and built-in functions
- Form handling and data validation
- MySQL database integration with PDO
- Sessions, cookies, and authentication
- File handling and uploads
- Object-oriented PHP and classes
Beginner
Python programming from beginner to confident developer. Learn Python syntax, control flow, functions, object-oriented programming, file I/O and popular standard library modules.
- Python syntax and data types
- Lists, tuples, dictionaries, and sets
- Control flow: if/elif/else, for, while
- Functions, lambda, and decorators
- Object-oriented programming in Python
- File handling and exceptions
- Modules, packages, and pip
- Introduction to NumPy and data manipulation
Intermediate
Comprehensive Java programming covering OOP principles, inheritance, interfaces, the Collections framework, generics, exception handling and introduction to Java applications.
- Java syntax and primitive types
- Classes, objects, and constructors
- Inheritance, polymorphism, abstraction
- Interfaces and abstract classes
- Collections: ArrayList, HashMap, Set
- Generics and type-safe programming
- Exception handling and custom exceptions
- File I/O and Java streams
Intermediate
Business intelligence and data visualization with Microsoft Power BI. Import data, build relationships, write DAX formulas and publish interactive dashboards.
- Introduction to business intelligence
- Connecting to data sources
- Power Query and data transformation
- Building relationships between tables
- DAX basics: calculated columns and measures
- Visualizations: charts, maps, slicers
- Creating and publishing dashboards
- Power BI Service and sharing reports
Intermediate
Introduction to AI covering search strategies, knowledge representation, logic, expert systems, natural language processing and an introduction to neural networks.
- Introduction to AI: history and goals
- Uninformed search: BFS, DFS
- Heuristic search: A*, hill climbing
- Knowledge representation and logic
- Expert systems and inference engines
- Natural language processing basics
- Computer vision overview
- Introduction to neural networks and deep learning
Advanced
Machine learning from theory to practice. Study regression, classification, clustering, dimensionality reduction, model evaluation and an introduction to deep learning.
- What is machine learning? Types and applications
- Linear and logistic regression
- Decision trees and random forests
- Support Vector Machines (SVM)
- Clustering: k-means, hierarchical
- Dimensionality reduction: PCA
- Model evaluation: accuracy, precision, recall, F1
- Introduction to deep learning and neural networks
Complete subject coverage for B.Tech / BCA / MCA students based on university syllabi. Each course includes unit-wise lessons aligned with semester examination requirements.
Arrays, linked lists, stacks, queues, trees, heaps, graphs, hashing, and sorting and searching algorithms with time complexity analysis.
Relational model, ER diagrams, SQL, normalization (1NF–BCNF), transactions, ACID properties, concurrency control, and query optimization.
Client-side and server-side web development with HTML, CSS, JavaScript, PHP, and MySQL. Covers the full web application development lifecycle.
IoT architecture, sensors and actuators, MQTT and CoAP protocols, edge and cloud computing, Arduino/Raspberry Pi, and real-world IoT case studies.
Hadoop ecosystem, HDFS, MapReduce, Apache Spark, data ingestion with Sqoop and Flume, HBase, and large-scale analytics pipelines.
Unix architecture, file system, essential commands, shell scripting (bash), process management, permissions, and system administration basics.
Principles of data visualization, chart types, Tableau, Power BI, storytelling with data, and building analytical dashboards.
Software testing lifecycle, black-box and white-box testing, unit testing, integration testing, test case design, and automation basics.
Types of disasters, risk assessment, mitigation strategies, emergency response, disaster recovery, and national disaster management frameworks.
Ecosystems, biodiversity, natural resources, environmental pollution, climate change, sustainability, and environmental laws and policies.
ATM networks, frame relay, SONET/SDH, MPLS, QoS, traffic management, broadband technologies and next-generation network architectures.
Data warehouse architecture, ETL processes, OLAP, data cubes, association rule mining, clustering, classification, and pattern discovery.