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Linux and Python Automation with Bash Scripting

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Course Brochure
Last Updated: 12/2025
Start Date Dec 15, 2025
Duration 120 Days
EMI Starting At ₹6250
Language Availability Both English & Hindi

Course Key Highlights:

Hours of Instructor-Led Training
Flexible Schedule
22 Hours of Self-Paced Videos
Certification
Job Assistance
Lifetime Free Upgrade
56 Hours of Projects Exercises
Hours of Instructor-Led Training
Why should you opt for this course?
  • Gain Comprehensive and Integrated Automation Expertise
  • . Focus on Practical, Portfolio-Ready Project Delivery
  • Preparation for High-Demand Career Paths in DevOps and Cloud:
  • Extensive Career Support and Flexible Learning Option

What will you learn?

  • Linux Administration Mastery.
  • Bash Scripting Expertise.
  • Python for Automation.
  • Integrated DevOps & Cloud Automation.

Who should enroll?

Freshers
Freshers

IT Freshers and Job Seekers build practical, integrated expertise for high-demand technical roles

Administrators
Administrators

System and IT Support staff master automation, scripting, and system maintenance tasks

Engineers
Engineers

Engineers

What are the prerequisites?

  • Basic knowledge of programming concepts or command-line interfaces
  • Familiarity with the Linux operating system (or a willingness to learn)
  • Being comfortable with terminal/command-line environments

What is the price?

₹30000 ₹25000
₹25000 Buy Now

Course Curriculum

Module 1: Linux Fundamentals 4 lectures

Learning Objectives:

  • Understand Linux architecture and distributions
  • Navigate Linux file system effectively
  • Master essential Linux commands
  • Configure users, permissions, and system settings 

Topics:

  1. Linux Basics
    1. Origins and key features of Linux
    2. Popular Linux distributions (Ubuntu, CentOS, RedHat, Debian)
    3. Linux architecture and components
    4. Kernel, shell, and file systems
  2. Getting Started with Linux
    1. Installing Linux distributions
    2. Terminal/Console basics
    3. Command-line interface navigation
    4. Man pages and help commands
  3. File System Navigation
    1. Directory structure and paths (absolute vs relative)
    2. pwd, ls, cd, mkdir, rmdir, rm commands
    3. File and directory creation/deletion
    4. Path shortcuts (., .., ~, /) 
  4. File Operations
    1. Creating, copying, moving, and renaming files (cp, mv, touch)
    2. File viewing and editing (cat, less, more, nano, vim)
    3. File permissions and ownership (chmod, chown)
    4. Understanding read, write, execute permissions
  5. User and Group Management
    1. Creating and managing users (useradd, userdel, usermod)
    2. Group management (groupadd, groupdel)
    3. Password management and sudo privileges
    4. Understanding superuser privileges
  6. Networking Basics
    1. IP addresses and network interfaces
    2. ping, ifconfig, netstat, traceroute commands
    3. SSH connection and key-basedauthentication
    4. Network troubleshooting basics Hands-on Activities:
    5. Lab 1.1: Linux Installation and Setup
    6. Lab 1.2: File System Navigation and Operations
    7. Lab 1.3: User Management and Permissions
    8. Project 1: Lin
Module 2: Linux Commands and Command-Line Tools 4 lectures

Learning Objectives:

  • Master essential Linux commands for daily operations
  • Understand pipes, filters, and command chaining
  • Work with text files and streams
  • Manage processes and system resources 

Topics:

  1. File Content Operations
    1. Displaying file content (cat, head, tail, wc)
    2. Searching within files (grep, egrep, fgrep)
    3. Sorting and uniqueness (sort,uniq)
    4. Pattern matching with grep
  2. Text Processing and Manipulation
    1. sed (Stream Editor) for text editing
    2. AWK for data extraction and formatting
    3. cut, tr, paste commands
    4. Regular expressions for pattern matching
  3. Piping and Input/Output Redirection
    1. Understanding pipes (|)
    2. Output redirection (>, >>)
    3. Input redirection (<)
    4. Error redirection (2>, 2>>)
    5. Combining stdout and stderr (2>&1)
  4. Process Management
    1. Listing processes (ps, top, htop)
    2. Process priorities and nice values
    3. Background and foreground processes
    4. Killing and managing processes (kill, pkill, killall)
    5. Process signals and exit codes
  5. System Monitoring and Performance
    1. CPU andmemory monitoring
    2. Disk usage (df, du)
    3. Network monitoring (netstat, ss, lsof)
    4. System logs and journalctl
    5. System performance analysis
  6. Compression and Archiving
    1. Compression tools (gzip, bzip2, xz)
    2. Archive creation (tar)
    3. tar with compression combinations
    4. Extracting and listing archives
  7.  Hands-on Activities:
    1. Lab 2.1: Text Processing with grep, sed, and AWK
    2. Lab 2.2: Piping and Redirection Techniques
    3. Lab 2.3: Process Management and Monitoring
    4. Lab 2.4: Log Analysis Project
  8. Project 2: System Performance Monitoring Dashboard
Module 3: Introduction to Bash Scripting 6 lectures

Learning Objectives:

  • Create executable shell scripts
  • Understand variables and data types
  • Implement conditional logic and loops
  • Work with user input and command-line arguments
  • Handle errors and exit codes

Topics:

  1. Shell Script Basics
    1. What is a shell script and when touse it
    2. Shebang (#!) interpreter directive
    3. Making scripts executable (chmod +x)
    4. Running scripts (direct execution, source, bash)
    5. Script file naming conventions
  2. Variables and Data Types
    1. Variable declaration and naming conventions
    2. String, numeric, and array variables
    3. Variable substitution ($variable, ${variable})
    4. Special variables ($0, $1, $@, $#, $?, $!)
    5. Environment variables vs local variables
    6. Variable scope and exporting
  3. Command-Line Arguments and User Input
    1. Passing arguments to scripts ($1, $2, $@, $*)
    2. Reading user input with read command
    3. read options (-p prompt, -s silent, -t timeout)
    4. Handling multiple inputs and options
    5. getopt and getopts for option parsing
  4. Conditional Statements
    1. if-else, elif structures
    2. Test command [ ] and [[ ]] conditions
    3. Comparison operators (-eq, -lt, -gt, -ne, -le, -ge)
    4. String comparisons (-z, -n, ==, !=, =~)
    5. File testing (-f, -d, -e, -r, -w, -x)
  5. Logical operators (-a, -o, ! || &&)
    1. Loops and Iteration
    2. for loops (C-style and list-based)
    3. while loops and until loops
    4. Loop control (break, continue)
    5. Nested loops
    6. loop patterns and best practices
  6. Arrays in Bash
    1. Array declaration and initialization
    2. Accessing array elements
    3. Array length and iteration
    4. Associative arrays (hash tables)
    5. Array operations and manipulation
  7. Functions in Bash
    1. Function declaration and syntax
    2. Passing parameters to functions
    3. Function return values and exit codes
    4. Local variables in functions
    5. Recursive functions
    6. Function libraries and sourcing
  8. Error Handling and Exit Codes
    1. Understanding exit codes and $?
    2. Conditional execution (&&, ||)
    3. Error checking and error messages
    4. trap command for signal handling
    5. try-catch patterns in bash 
  9. Hands-on Activities:
    1. Lab 3.1: Writing Basic Bash Scripts
    2. Lab 3.2: User Input and Command-Line Arguments
    3. Lab 3.3: Conditional Logic and Loops
    4. Lab 3.4: Functions and Error Handling
  10. Project 3: System Administration Script 
    1. Project 3A: Log Analyzer Script
      1. Read log files and extract information
      2. Parse error messages and count occurrences
      3. Generate summary reports
      4. Implement error handling 
    2. Project 3B: Backup and Restore Script
      1. Create backup functionality with compression
      2. Archive directory structures
      3. Implement restore capability
      4. Schedule automated backups 
    3. Project 3C: User Management Utility
      1. Create users and groups programmatically
      2. Set permissions automatically
      3. Validate inputs and handle errors
      4. Generate user reports
Module 4: Advanced Bash Scripting and Text Processing 6 lectures

Learning Objectives:

  • Master advanced bash constructs
  • Implement text processing pipelines
  • Use sed and AWK for data manipulation
  • Create reusable, modular scripts
  • Debug and optimize scripts 

Topics:

  1. String Manipulation in Bash
    1. String concatenation and interpolation
    2. String length and substring operations
    3. Pattern matching and string replacement
    4. Case conversion and trimming
    5. String validation and formatting
  2. Regular Expressions (Regex)
    1. Regex syntax and metacharacters
    2. Basic and extended regex patterns
    3. Character classes and quantifiers
    4. Anchors and word boundaries
    5. Grouping and backreferences
    6. Practical regex examples
  3. sed - Stream Editor
    1. sed syntax and options
    2. Substitution (s command)
    3. Address ranges and patterns
    4. Deleting, appending, and inserting lines
    5. sed scripts and command files
    6. sed in automation pipelines
  4. AWK - Data Processing
    1. AWK syntax and structure (BEGIN, body, END)
    2. Fields and records
    3. Pattern matching with AWK
    4. Variables and arrays in AWK
    5. User-defined functions in AWK
    6. AWK one-liners for common tasks
  5. Advanced Control Structures
    1. case statements for multi-way branching
    2. select loops for menu creation
    3. getopts for robust option parsing
    4. Complex conditionals and nesting
  6. File I/O and Stream Processing
    1. Reading and writing files in scripts
    2. Redirecting file descriptors
    3. Here documents and here strings
    4. Process substitution
    5. Named pipes (FIFOs)
  7. Script Debugging and Optimization
    1. Bash debugging modes(-x, -v)
    2. Using set command for debugging
    3. Script profiling and performance
    4. Common pitfalls and best practices
    5. Code optimization techniques
  8. Configuration Files and Scripts
    1. Sourcing external files and libraries
    2. Configuration file parsing
    3. Creating reusable function libraries
    4. Best practices for script organization
  9.  Hands-on Activities:
    1. Lab 4.1: String Manipulation and Regex Patterns
    2. Lab 4.2: sed for Log File Processing
    3. Lab 4.3: AWK for Data Analysis
    4. Lab 4.4: Advanced Script Development
  10. Project 4: Configuration Management Tool 
    1. Project 4A: Log Rotation and Archival System
      1. Monitor log file sizes
      2. Compress old logs with date stamps
      3. Remove old archives
      4. Send notifications on completion 
    2. Project 4B: System Monitoring Dashboard
      1. Collect CPU, memory,disk metrics
      2. Format data with AWK
      3. Generate HTML reports
      4. Email reportson schedule
    3.  Project 4C: Data Processing Pipeline
      1. Parse CSV/structured data
      2. Filter and transform data with sed/AWK
      3. Generate summary statistics
      4. Export in multiple formats
Module 5: Python for System Automation 7 lectures

Learning Objectives:

  • Master Python fundamentals for automation
  • Work with file systems and processes
  • Implement data structures and algorithms
  • Create object-oriented automation scripts
  • Integrate Python with system commands 
  •  

Topics:

  1. Python Basics for Automation
    1. Python installation and environment setup
    2. IDE setup (PyCharm, VS Code)
    3. Python syntax and best practices
    4. Running Python scripts
    5. Virtual environments and package management
  2. Python Data Types and Variables
    1. Strings, integers, floats, booleans
    2. Lists, tuples, dictionaries, sets
    3. Type conversion and checking
    4. Variable naming conventions
    5. Immutable vs mutable types
  3. Control Flow and Functions
    1. if-elif-else statements
    2. for and while loops
    3. List comprehensions and generators
    4. Function definition and parameters
    5. Default arguments and keyword arguments
    6. Variable scope and global/local variables
  4. File and Directory Operations
    1. Opening, reading, writing files
    2. Working with file paths (pathlib)
    3. Directory operations and walking
    4. File permissions and metadata
    5. Context managers and file handling best practices
  5. Regular Expressions in Python
    1. re module and pattern matching
    2. Search, match, findall, finditer
    3. Substitution and text replacement
    4. Compiling regex patterns for performance
    5. Practical regex examples
  6. Working with System Processes
    1. subprocess module for process execution
    2. Running shell commands from Python
    3. Capturing stdout and stderr
    4. Process management and communication
    5. Pipes and inter-process communication
  7. Object-Oriented Programming
    1. Classes and objects
    2. Methods and attributes
    3. Inheritance and polymorphism
    4. Encapsulation and access modifiers
    5. Designing automation classes
  8. Data Processing and Manipulation
    1. Working with CSV files (csv module)
    2. JSON parsing and generation
    3. Structured data handling
    4. List, dictionary, and set operations
    5. Sorting and filtering data 
  9. Hands-on Activities:
    1. Lab 5.1: Python Fundamentals
    2. Lab 5.2: File Operations and Directory Management
    3. Lab 5.3: System Process Automation
    4. Lab 5.4: Data Processing with Python
  10. Project 5: System Administration Tool
    1. Project 5A: File System Backup Tool
      1. Recursively scan directories
      2. Calculate file hashes for deduplication
      3. Create backup archives
      4. Implement incremental backup logic 
    2. Project 5B: System Information Collector
      1. Gather CPU, memory,disk information
      2. Parse /proc filesystem
      3. Generate detailed reports
      4. Export to multiple formats (JSON,CSV, HTML) 
    3. Project 5C: Automated Task Scheduler
      1. Create task definitions
      2. Schedule execution based on triggers
      3. Log execution results
      4. Handle dependencies between tasks
Module 6: Integration of Bash and Python for Automation 5 lectures

Learning Objectives:

  • Combine Bash and Python for powerful automation
  • Create hybrid scripts and workflows
  • Implement end-to-end automation solutions
  • Work with APIs and external services
  • Scale automation for enterprise environments

Topics:

  1. Calling Python from Bash Scripts
    1. Executing Python scripts from Bash
    2. Passing arguments and capturing output
    3. Error handling and exit codes
    4. Environment variable passing
  2. Calling Bash from Python
    1. subprocess.run() for Bash commands
    2. Running complex shell pipelines
    3. Shell features in Python scripts
    4. Performance considerations
  3. Data Exchange Between Bash and Python
    1. Passing data through pipes
    2. Using JSON for data interchange
    3. File-based data exchange
    4. Environment variables and configuration
  4. API Integration and Automation
    1. HTTP requests and REST APIs
    2. Authentication and headers
    3. Parsing JSON responses
    4. Error handling and retries
    5. Webhook and automation triggers
  5. Scheduled Automation with Cron
    1. Cron syntax and scheduling
    2. Creating and managing cron jobs (crontab)
    3. Running Bash and Python scripts via cron
    4. Logging and monitoring scheduled tasks
    5. Handling dependencies and timing
  6. Advanced Monitoring and Alerting
    1. System event monitoring
    2. Alert generation and notification
    3. Email notifications (SMTP)
    4. Integration with monitoring tools
    5. Log aggregation and analysis
  7. Enterprise Automation Patterns
    1. Infrastructure as Code (IaC) concepts
    2. Configuration management scripts
    3. Deployment automation
    4. Multi-server orchestration
    5. Error recovery and rollback procedures

Hands-on Activities:

  • Lab 6.1: Bash-Python Integration
  • Lab 6.2: API Automation with Python
  • Lab 6.3: Cron JobManagement and Scheduling
  • Lab 6.4: Enterprise Automation Solution
  • Project 6: Complete Automation Platform 

Project 6A: AWS Resource Monitoring System

  • Fetch AWS resources using AWS CLI
  • Parse output with Bash and Python
  • Generate reports and alerts
  • Integrate with email notifications 

Project 6B: Deployment Automation Pipeline

  • Validate code and configuration
  • Execute pre-deployment checks
  • Perform staged deployment
  • Rollback on failure

Project 6C: Log Analysis and Alerting System

  • Monitor multiple log files
  • Detect anomalies and errors
  • Generate alerts basedon patterns
  • Create actionable reports
Module 7: DevOps Automation and Real-World Applications 6 lectures

Learning Objectives:

  • Apply automation to DevOps workflows
  • Implement CI/CD automation
  • Manage infrastructure with scripts
  • Work with cloud platforms (AWS, Azure, GCP)
  • Create production-grade automation solutions 

Topics:

  1. Infrastructure Automation
    1. Infrastructure as Code (IaC) principles
    2. Server provisioning scripts
    3. Configuration management automation
    4. Environment consistency and reproducibility
  2. DevOps Pipeline Automation
    1. Build automation scripts
    2. Deployment orchestration
    3. Release management automation
    4. Health checks and monitoring integration
  3. Container and Kubernetes Automation
    1. Docker automation and image building
    2. Container deployment scripts
    3. Kubernetes resource management
    4. Pod and cluster monitoring
  4. Cloud Platform Automation (AWS Example)
    1. AWS CLI automation
    2. EC2 instance management
    3. S3 bucket operations
    4. RDS database automation
    5. Lambda function management
  5. Configuration Management
    1. Configuration file automation
    2. Environment variable management
    3. Secret and credentials handling
    4. Compliance checking and enforcement
  6. Database Automation
    1. Database backup and restore
    2. Schema migration scripts
    3. Data cleanup and maintenance
    4. Performance optimization automation
  7. Security Automation
    1. Security scanning and compliance checks
    2. Certificate management automation
    3. Access control automation
    4. Audit logging and reporting 

Hands-on Activities:

  1. Lab 7.1: Infrastructure Provisioning Script
  2. Lab 7.2: CI/CD Pipeline Automation
  3. Lab 7.3: AWS Resource Automation
  4. Lab 7.4: Production Deployment Workflow
  5. Project 7: End-to-End DevOps Pipeline 

Project7A: Multi-Environment Deployment Orchestrator

  • Manage development, staging, production environments
  • Validate configuration across environments
  • Automate deployment process
  • Implement rollback mechanisms

 Project 7B: Cloud Resource Cost Optimizer

  • Identify unused resources
  • Right-size instances and volumes
  • Generate cost reports
  • Implement cost optimization recommendations 

Project 7C: Security Compliance Automation

  • Scan for security vulnerabilities
  • Check compliance policies
  • Generate compliance reports
  • Automate remediation where possible

Course Projects

Project 1: Comprehensive System Health Monitor

Project 1: Comprehensive System Health Monitor Difficulty: Intermediate | Duration: 2-3 days Create a complete system monitoring solution combining Bash and Python: Monitor CPU, memory, disk, and network metrics Parse system logs for errors and warnings Generate customizable alerts Create daily/weekly reports Integrate with email notifications Technologies: Bash, Python, cron, email

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Project 2: Automated Backup and Disaster Recovery System

Difficulty: Intermediate-Advanced | Duration: 3-4 days Build a robust backup solution: Incremental and full backup capabilities Data verification and integrity checking Automated restoration procedures Multi-location backup support Recovery time objective (RTO) testing Technologies: Bash, tar, rsync, Python, AWS S3

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Project 3: CI/CD Pipeline Automation

Difficulty: Advanced | Duration: 4-5 days Develop an automated deployment pipeline: Code checkout and build automation Automated testing integration Staged deployment process Health checks and rollback Deployment notifications and reporting Technologies: Bash, Python, Git, Jenkins/GitHub Actions

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Project 4: Infrastructure as Code (IaC) Tool

Difficulty: Advanced | Duration: 4-5 days Create an infrastructure provisioning system: Define infrastructure in configuration files Automated server provisioning Application deployment Configuration management Environment consistency validation Technologies: Bash, Python, AWS CLI, CloudFormation/Terraform

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Project 5: Log Aggregation and Analysis Platform

Difficulty: Advanced | Duration: 5-6 days Build a centralized log management solution: Collect logs from multiple servers Parse and index log data Real-time search and analysis Anomaly detection Visualization and reporting Technologies: Bash, Python, sed, AWK, Elasticsearch

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Frequently Asked Question

This comprehensive course equips learners with practical expertise in Linux administration, Python programming, and Bash scripting to automate and manage modern IT environment

The course is aimed at System Administrators, DevOps Engineers, IT Support Professionals, Cloud Infrastructure Specialists, Software Engineers seeking automation skills, and IT Freshers/Job Seekers

No, this course is designed for beginners, although basic command-line familiarity is helpful but not required

You need a computer (Linux, Windows, or Mac OS) with a minimum of 4GB RAM and 20GB disk space, administrative access for software installation, and an internet connection (minimum 5 Mbps

Career Scope?

    • Linux System Administrator / Automation Engineer

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Your Instructors

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Manthan

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Person

Abhinav Thakur

Senior Full Stack Developer with 10+ years of extensive experience in designing, developing, and deploying scalable web applications across modern tech stacks. Skilled in leading projects, mentoring teams, and delivering high-quality solutions.