What you’ll learn
Introduction and importance of this course in this day and age
Approach all essential concepts from the beginning
Clear unfolding of concepts with examples in Python,Scrapy, Scala, PySpark and MongoDB
All theoretical explanations followed by practical implementations
Data Scraping & Data Mining for Beginners to Pro with Python
Master Big Data with Scala and Spark
Master Big Data With PySpark and AWS
Mastering MongoDB for Beginners
Building your own AI applications
Welcome to the comprehensive Big Data and Data Science bundle, where you’ll embark on an educational journey covering a wide range of essential skills and technologies. This course equips you with expertise in Scala, PySpark, AWS, Data Scraping, Data Mining, and MongoDB. Whether you’re an absolute beginner or possess some programming knowledge, this course provides in-depth coverage of these critical topics.
I. Scala:
Scala may not be the most popular coding language, but it’s undeniably one of the most sought-after skills for data scientists and data engineers. This course is meticulously designed to make Scala simple to grasp and implement. You’ll engage with quizzes and mini-projects to reinforce your learning, making your Scala experience seamless.
Key Highlights:
High Demand Skill: Scala is in high demand in the industry, and this course ensures you acquire essential skills
Practical Learning: Quizzes and mini-projects serve as building blocks for a comprehensive understanding of Scala
Hands-on Experience: Gain practical experience by working on a Scala Spark project
Versatility: Scala is a powerful language suitable for a wide range of applications, from web development to machine learning
Learning Materials:
Comprehensive Scala tutorials
Scala quizzes and assessments
Hands-on Scala Spark project
Scala code examples and exercises
II. PySpark and AWS:
Python and Apache Spark are at the forefront of Big Data analytics, and PySpark bridges the gap between them. In this section, you’ll start with the basics and progress to advanced data analysis. You’ll work with PySpark for data analysis, explore Spark RDDs, Dataframes, and Spark SQL queries, and delve into Spark and Hadoop ecosystems. Additionally, you’ll discover how to leverage AWS cloud services with Spark.
Key Highlights:
Python and Spark Integration: Master the art of using Python and Spark together for effective Big Data analysis
Comprehensive Coverage: Explore Spark RDDs, Dataframes, Spark SQL queries, and seamlessly integrate with AWS
Hands-on Practice: Apply your knowledge through practical exercises and projects
Learning Materials:
In-depth PySpark and AWS tutorials
PySpark quizzes and assessments
AWS integration guides and examples
PySpark code samples and hands-on projects
III. Data Scraping and Data Mining:
Data scraping involves extracting data from websites and APIs, making it a valuable skill for data professionals. This section is tailored for beginners, starting with foundational concepts and gradually delving into advanced techniques through practical implementations. Hands-on projects are a pivotal part of this segment, allowing you to learn through experimentation and real-world applications.
Key Highlights:
Beginner-Friendly: Perfect for individuals new to data scraping and mining
Practical Implementation: Gain deep insights through hands-on projects and real-world examples
Lucrative Career: Data scraping offers rewarding career prospects and competitive salaries
Learning Materials:
Comprehensive Data Scraping and Mining tutorials
Hands-on data extraction projects
Data scraping and mining quizzes and assessments
Data scraping code samples and automation scripts
IV. MongoDB:
This section introduces you to MongoDB, a popular NoSQL database. You’ll learn the fundamentals of MongoDB, including Create, Read, Update, and Delete operations. Dive deep into MongoDB query and project operators, enhancing your understanding of NoSQL databases. Two comprehensive projects will provide you with practical experience using MongoDB in Django and implementing an ETL (Extract, Transform, Load) pipeline with PySpark.
Key Highlights:
NoSQL Proficiency: Develop expertise in MongoDB, a highly sought-after NoSQL database
Hands-on Projects: Apply your knowledge to real-world scenarios and gain practical skills
Versatile Skills: MongoDB is invaluable for data management and analytics
Learning Materials:
MongoDB fundamentals and advanced tutorials
Hands-on MongoDB projects, including Django integration and ETL pipeline development
MongoDB quizzes and assessments
MongoDB code examples and best practices
Course Benefits:
Upon completing this comprehensive course successfully, you will be proficient in implementing projects from scratch that require expertise in Data Scraping, Data Mining, Scala, PySpark, AWS, and MongoDB. You’ll be adept at connecting theoretical concepts to real-world problem-solving, efficiently extracting data from websites, and be well-prepared for various data-related roles.
Learning Materials:
Video lectures and tutorials.
Quizzes, assessments, and solutions.
Hands-on projects with step-by-step guidance.
Code examples and templates.
Reference materials and best practices.
Enroll now to embark on your journey toward mastering Big Data and Data Science comprehensively!
Who Should Enroll:
Ideal for beginners or those looking to apply theoretical knowledge in practical scenarios
Aspiring data scientists and machine learning experts
Individuals aiming to excel in the realm of Big Data and Data Science
What You’ll Learn:
Proficiency in implementing projects requiring expertise in Data Scraping, Data Mining, Scala, PySpark, AWS, and MongoDB
Efficient data extraction from websites
Skills applicable to various data-related roles
Why This Course:
High demand for Scala skills in the industry
Comprehensive coverage of PySpark, AWS, Data Scraping, Data Mining, and MongoDB
Hands-on experience through projects and practical exercises
Versatile skills for a wide range of applications
List of Keywords:
Big Data
Data Science
Scala
PySpark
AWS
Data Scraping
Data Mining
MongoDB
NoSQL Database
Data Extraction
Data Analysis
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File size: 24.9GB
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| Weight | 1.00 kg |
|---|---|
| Dimensions | 1.00 × 1.00 × 1.00 cm |
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