Soumya Parida

Years of Experience in Unix Shell Scripting Training classes

10

Years of Experience in Big Data Training

6

Teaching Experience in detail in Big Data Training

I teach Big data technologies like Hadoop,Python,Pyspark,AWS(lambda,S3,Redshift,Glue,Step Functions,Event Bridge,Cloud Watch,Databricks)

Years of Experience in SQL Server Training

10

Teaching Experience in detail in SQL Server Training

1. Basic SQL DDL, DML, DCL, TCL CREATE, ALTER, DROP SELECT, INSERT, UPDATE, DELETE 2. Built-in SQL Functions String Functions: UPPER(), LOWER(), SUBSTR(), CONCAT(), TRIM() Numeric Functions: ROUND(), CEIL(), FLOOR(), MOD(), ABS() Date Functions: SYSDATE, GETDATE(), ADD_MONTHS(), DATEDIFF(), DATEPART() Conversion Functions: TO_CHAR(), TO_DATE(), CAST(), CONVERT() Aggregate Functions: SUM(), AVG(), COUNT(), MAX(), MIN() 3. Joins INNER JOIN LEFT JOIN RIGHT JOIN FULL OUTER JOIN CROSS JOIN SELF JOIN 4. Subqueries Single-row subqueries Multi-row subqueries Scalar subqueries Correlated subqueries Nested subqueries EXISTS, NOT EXISTS 5. Set Operators UNION UNION ALL INTERSECT MINUS (SQL*Plus) EXCEPT (SQL Server) 6. Views and Indexes CREATE VIEW MATERIALIZED VIEW (SQL*Plus) INDEX types: clustered, non-clustered, bitmap (SQL*Plus) 7. Window Functions ROW_NUMBER() RANK() DENSE_RANK() NTILE() LEAD() LAG() 8. Analytical Functions SUM() OVER(...) AVG() OVER(...) FIRST_VALUE() LAST_VALUE() PERCENT_RANK() CUME_DIST() 9. Stored Procedures CREATE PROCEDURE (SQL Server / SQL*Plus) Parameters: IN, OUT, IN OUT Execution methods Cursors Exception handling Transactions Dynamic SQL Nested procedures System stored procedures (SQL Server)

Years of Experience in C Language Classes

10

Teaching Experience in detail in C Language Classes

C Programming – Syllabus 1. Introduction to C History of C Structure of a C program Compilation and execution process 2. Data Types and Variables Basic data types: int, float, char, double Derived data types: array, pointer, structure, union Storage classes: auto, static, register, extern 3. Operators and Expressions Arithmetic operators Relational operators Logical operators Bitwise operators Assignment and compound operators Increment and decrement operators Conditional (?:) operator 4. Control Flow Statements if, if-else nested if switch-case goto statement 5. Looping Constructs while loop do-while loop for loop break and continue statements 6. Arrays and Strings One-dimensional arrays Multi-dimensional arrays String input/output String functions: strlen(), strcpy(), strcat(), strcmp() 7. Functions Function declaration and definition Call by value and call by reference Recursion Scope and lifetime of variables 8. Pointers Pointer declaration and initialization Pointer arithmetic Pointers and arrays Pointers to functions Pointers to structures 9. Structures and Unions Defining structures Nested structures Array of structures Union declaration and usage 10. File Handling File operations: fopen(), fclose(), fread(), fwrite(), fprintf(), fscanf() File modes Text vs binary files 11. Dynamic Memory Allocation malloc(), calloc(), realloc(), free() 12. Preprocessor Directives #define, #include Conditional compilation Macros 13. Miscellaneous Topics Command-line arguments Enumerations Typedef Error handling (errno, perror())

Years of Experience in Python Training classes

10

Teaching Experience in detail in Python Training classes

Core Python – Syllabus 1. Introduction to Python History and Features Installing Python Python IDEs Writing and executing the first Python script 2. Python Basics Variables and Data Types Input and Output Comments Type Casting 3. Operators Arithmetic Operators Comparison Operators Logical Operators Assignment Operators Bitwise Operators Identity and Membership Operators 4. Control Flow if, if-else, elif Nested if statements while loop for loop break, continue, pass 5. Data Structures Lists Tuples Sets Dictionaries 6. String Handling String methods String formatting Escape characters f-strings 7. Functions Defining functions Function arguments return statement Lambda functions *args and **kwargs Recursion 8. Modules and Packages Importing modules Creating user-defined modules Built-in modules (math, random, etc.) __name__ == '__main__' 9. File Handling Opening and closing files Reading and writing text and binary files File methods With statement CSV file handling 10. Exception Handling try, except else, finally Multiple exceptions Custom exceptions 11. Object-Oriented Programming Classes and Objects __init__ method Inheritance Method Overriding Encapsulation and Abstraction @classmethod and @staticmethod 12. Python Built-in Functions Common built-ins: len(), range(), type(), id(), isinstance(), etc. Map, Filter, Reduce Enumerate, Zip 13. Comprehensions List comprehension Dictionary comprehension Set comprehension 14. Iterators and Generators __iter__() and __next__() Creating generators using yield 15. Working with Libraries math, datetime, random, os, sys 16. Introduction to Virtual Environment & pip Creating and activating virtual environments Installing packages using pip Python for Data Analysis – Syllabus 1. Introduction to Data Analysis with Python Overview of Data Analysis Setting up Python for Data Science (Anaconda, Jupyter, Pandas, NumPy, Matplotlib) 2. Python Libraries for Data Analysis Introduction to NumPy Introduction to Pandas Introduction to Matplotlib and Seaborn Introduction to SciPy Introduction to Scikit-learn 3. Data Structures for Data Analysis NumPy Arrays Pandas Series and DataFrames Indexing and Slicing with Pandas Data Alignment and Missing Data 4. Data Wrangling Loading data from CSV, Excel, SQL, JSON Data Cleaning: Handling Missing Values Renaming, Dropping, and Filtering Data Type Conversion and Data Transformation Merging, Joining, and Concatenating DataFrames 5. Data Exploration and Descriptive Statistics Basic Descriptive Statistics Grouping and Aggregating Data Pivot Tables Summary Statistics using Pandas Data Visualizations: Histograms, Box Plots, and Scatter Plots 6. Data Visualization with Matplotlib and Seaborn Basic Plots with Matplotlib Customizing Plots (Labels, Titles, Legends, Colors) Seaborn Plots: Heatmaps, Pair Plots, and Regression Plots Advanced Visualizations: Subplots, Styles 7. Exploratory Data Analysis (EDA) Understanding Data Distribution Correlation Analysis Feature Selection Identifying Outliers Univariate and Bivariate Analysis 8. Handling Time Series Data Working with Date and Time in Pandas Time Series Indexing and Resampling Moving Averages and Rolling Statistics Time Series Decomposition 9. Statistical Analysis and Hypothesis Testing Probability Distributions Central Limit Theorem T-tests, ANOVA, Chi-square Tests P-value and Confidence Intervals 10. Introduction to Machine Learning Supervised vs Unsupervised Learning Introduction to Regression and Classification Preparing Data for Machine Learning Training and Testing Models using Scikit-learn 11. Data Analysis Project End-to-End Data Analysis Project From Data Collection to Visualization Model Building and Evaluation 12. Advanced Topics (Optional) Feature Engineering and Selection Clustering Techniques (K-means, DBSCAN) Introduction to Deep Learning with TensorFlow/Keras Python for Files and Other Automations – Syllabus 1. Introduction to Automation with Python What is Automation? Setting up Python for automation tasks Overview of libraries used for automation: os, shutil, glob, subprocess, etc. 2. Working with Files Opening and Closing Files Reading Files: read(), readlines() Writing to Files: write(), writelines() File Modes: Read, Write, Append Working with File Paths: os.path, glob 3. Directory and File Management Creating, Renaming, and Deleting Files Managing Directories: mkdir(), rmdir(), chdir() Listing Directory Contents: os.listdir(), glob.glob() Moving, Copying, and Deleting Files: shutil.move(), shutil.copy(), shutil.rmtree() File Permissions 4. Automating Tasks with OS Module Interacting with Operating System using os.system() Environment Variables Working with Shell Commands in Python Managing Processes with subprocess 5. Automating Email Sending Sending Emails with smtplib Formatting Emails (Text/HTML) Sending Attachments with Emails Automating Reports via Email 6. Automating Web Scraping Introduction to Web Scraping with requests and BeautifulSoup Extracting Data from Web Pages Navigating HTML Structure Storing Data from Web Scraping (CSV, JSON) Handling CAPTCHAs and Anti-Scraping Measures 7. Automating Data Entry and Forms Using pyautogui for GUI Automation Automating Form Filling Automating Mouse and Keyboard Inputs Automating Browsers with Selenium 8. Working with APIs Introduction to REST APIs Sending GET and POST requests Authentication (API keys, OAuth) Parsing JSON data Automating API Calls (e.g., for data retrieval, sending data) 9. Automating File Handling Renaming Multiple Files Batch File Operations (Move, Copy, Delete) Automating File Backups Monitoring File Changes using watchdog 10. Scheduling Automation Tasks Scheduling Tasks with schedule module Automating Daily/Weekly Jobs Automating Python Scripts with Cron (Linux) or Task Scheduler (Windows) 11. Advanced Automation Topics Automating GUI Applications with pywinauto Automating Report Generation (Excel, CSV, PDF) Sending Automated Reminders and Alerts Automating Data Backup Systems Web Crawlers for Periodic Data Retrieval 12. Real-world Automation Projects Automating Daily Report Generation Automating File Organization Web Scraping for Data Collection and Analysis Automating Social Media Posts or Notifications

Years of Experience in Java Training Classes

6

Teaching Experience in detail in Java Training Classes

Core Java – Syllabus 1. Introduction to Java History of Java Features of Java Setting up Java Development Environment Writing and Running a Simple Java Program 2. Java Data Types and Variables Primitive Data Types: int, float, double, char, boolean, etc. Variables: Declaration and Initialization Type Casting and Type Conversion Constants (final keyword) 3. Operators in Java Arithmetic Operators Relational Operators Logical Operators Assignment Operators Bitwise Operators Conditional (Ternary) Operator 4. Control Flow Statements if, if-else, nested if switch-case break, continue, and return statements 5. Loops in Java for loop while loop do-while loop Enhanced for loop (foreach) 6. Arrays in Java One-dimensional arrays Multi-dimensional arrays Array initialization and traversal Arrays and Memory 7. Methods in Java Method Declaration and Definition Method Overloading Variable Arguments (Varargs) Recursion 8. Object-Oriented Programming Concepts Classes and Objects Constructors and Constructor Overloading Method Overloading and Method Overriding this keyword super keyword 9. Inheritance in Java Extending Classes Method Overriding super() and super keyword Multilevel and Hierarchical Inheritance Constructor Chaining 10. Polymorphism Method Overloading vs Method Overriding Runtime Polymorphism (Dynamic Method Dispatch) Static vs Dynamic Binding 11. Abstraction and Encapsulation Abstract Classes and Methods Interfaces and their Implementation Access Modifiers: private, public, protected, and default Getters and Setters (Encapsulation) 12. Exception Handling try, catch, finally block throw and throws keyword Custom exceptions Multiple Catch blocks Exception Hierarchy 13. Collections Framework List: ArrayList, LinkedList Set: HashSet, TreeSet Map: HashMap, TreeMap Iterator Interface ListIterator Collection Interfaces: Collection, Set, List, Queue 14. Java I/O File I/O: File, FileReader, FileWriter, BufferedReader, BufferedWriter Byte Streams: InputStream, OutputStream Object Serialization: ObjectInputStream, ObjectOutputStream Reading/Writing Text and Binary Files 15. Multithreading in Java Creating Threads (Extending Thread class, Implementing Runnable Interface) Thread Lifecycle and States Synchronization and Thread Safety Thread Intercommunication (wait, notify, notifyAll) 16. Java 8 Features Lambda Expressions Functional Interfaces Streams API Default Methods in Interfaces Method References Optional Class 17. Java Memory Management Memory Areas: Stack, Heap Garbage Collection in Java Finalization and finalize() method 18. Java Networking Introduction to Networking in Java Sockets Programming (Client-Server model) URL and HTTP Connections TCP/IP and UDP Protocols 19. JDBC (Java Database Connectivity) Introduction to JDBC Connecting to Databases Executing SQL Queries (Insert, Update, Select, Delete) PreparedStatement and ResultSet Transactions and Connection Pooling 20. Java Design Patterns (Optional) Singleton Pattern Factory Pattern Observer Pattern Strategy Pattern Decorator Pattern