Anurag Singh Data Scientist, Excel, Python, HTML, Java, Hadoop,
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Title: Big Data Engineer Curriculum

Module 1: Introduction to Big Data Engineering
- Overview of Big Data and its significance
- Understanding the role of a Big Data Engineer
- Tools and technologies in Big Data engineering
- Setting up your development environment (Linux, Python, Java)

Module 2: Python Programming for Big Data
- Python basics and data structures
- Data manipulation with NumPy and Pandas
- Data visualization with Matplotlib and Seaborn
- Working with JSON and XML data in Python

Module 3: HTML and Web Scraping
- Introduction to HTML and web technologies
- Web scraping using BeautifulSoup and Requests
- Storing scraped data in various formats
- Building a web-based dashboard with HTML and JavaScript

Module 4: Java for Big Data
- Java fundamentals and object-oriented programming
- Handling large datasets with Java
- Working with Hadoop and MapReduce
- Building custom Java applications for Big Data processing

Module 5: SQL for Data Management
- Relational databases and SQL basics
- Advanced SQL queries for data extraction
- Indexing and optimization techniques
- Introduction to NoSQL databases (MongoDB, Cassandra)

Module 6: Linux for Big Data Engineering
- Linux essentials and command-line basics
- Shell scripting for automation
- Managing distributed systems on Linux servers
- Security and permissions in a Linux environment

Module 7: Excel for Data Analysis
- Excel basics and data importing
- Data cleaning and transformation in Excel
- Building PivotTables and PivotCharts
- Using Excel for exploratory data analysis

Module 8: Big Data Processing Frameworks
- Introduction to Apache Hadoop and Spark
- Distributed data processing with Hadoop MapReduce
- Real-time data processing with Spark Streaming
- Building data pipelines with Apache Kafka

Module 9: Data Warehousing and ETL
- Understanding data warehousing concepts
- Designing ETL (Extract, Transform, Load) processes
- Implementing ETL workflows with tools like Apache NiFi
- Data integration and data quality considerations

Module 10: Data Visualization and Reporting
- Data visualization principles and best practices
- Creating interactive dashboards with Tableau or Power BI
- Communicating insights effectively through data visualization
- Project: Build a data-driven dashboard

Module 11: Big Data Security and Ethics
- Data privacy and ethical considerations in Big Data
- Security best practices for Big Data systems
- Implementing access control and encryption
- Compliance with data protection regulations (e.g., GDPR)

Module 12: Capstone Project
- Apply the skills learned throughout the course
- Choose a real-world Big Data problem to solve
- Develop a comprehensive solution using Python, Java, SQL, and other tools
- Present and document the project results

This curriculum covers a wide range of topics and skills required for a Big Data Engineer, including programming languages (Python, Java), data manipulation (SQL), web technologies (HTML), operating systems (Linux), and data analysis (Excel). It also includes practical hands-on projects to reinforce learning and prepare students for real-world scenarios.

Subjects

  • HTML CSS and JavaScript Beginner-Expert

  • Python and Kafka Beginner-Expert

  • Linux Administration Beginner-Expert

  • Data Analysis with Excel, Access and sql Beginner-Expert

  • Hadoop Big Data Beginner-Expert

Experience

  • Big data Engineer (Jun, 2017–Present) at Bharti Airtel
    I am working as a big data engineer since 5 years, I have a good command on python, HTML, CSS, Java script, MongoDB, Hadoop, Excel, Linux, SQL.

Education

  • B.Tech (Jul, 2011–Aug, 2015) from Azad institute of engineering and technology, Lucknow

Fee details

    ₹1,200–2,000/hour (US$14.21–23.69/hour)

    Fee Can vary as per time, if I wil be free I will chrage less, if you are 4 to 5 people, we can negotiate. eg. Per person 500/hour Inr

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