Course Details

Tame the Data Deluge: Big Data Analytics with Python & R Training Course

INTRODUCTION

In the era of information overload, the ability to extract meaningful insights from massive datasets is a critical skill. This Big Data Analytics with Python & R Training Course equips participants with the tools and techniques to conquer the challenges of big data. You'll learn to leverage the power of Python and R, two of the most popular languages for data science, to process, analyze, and visualize large datasets. This program is designed to empower you to transform raw data into actionable intelligence, driving informed decisions and strategic advantage.

DURATION

5 days

TARGET AUDIENCE

This course is designed for:

• Data analysts and scientists seeking to expand their big data skills.
• Software developers and engineers working with large datasets.
• Business intelligence professionals and data-driven decision-makers.
• Researchers and academics dealing with massive data.
• Anyone looking to gain practical experience in big data analytics using Python and R.

COURSE OBJECTIVES

Upon completion of this course, participants will be able to:

• Understand the fundamental concepts of big data and its challenges.
• Utilize Python and R for big data processing and analysis.
• Implement distributed computing frameworks (e.g., Spark) for large-scale data processing.
• Perform data cleaning, transformation, and feature engineering on big datasets.
• Apply statistical analysis and machine learning techniques to big data.
• Create compelling data visualizations to communicate insights effectively.
• Understand the ethical considerations in big data analytics.
• Deploy big data analytics solutions in real-world scenarios.

COURSE MODULES

• Introduction to Big Data and its Ecosystem:
• Defining big data and its characteristics (volume, velocity, variety, veracity).
• Exploring the big data ecosystem and its components (Hadoop, Spark, cloud platforms).
• Understanding the challenges and opportunities of big data analytics.
• The history of big data.
• Python for Big Data Processing:
• Utilizing Python libraries for data manipulation (Pandas, NumPy).
• Implementing data cleaning and transformation techniques.
• Working with large datasets using chunking and lazy evaluation.
• Connecting to big data storage systems.
• R for Statistical Analysis and Visualization:
• Utilizing R for statistical modeling and analysis.
• Implementing data visualization using R libraries (ggplot2).
• Performing statistical tests and hypothesis testing on large datasets.
• Understanding how to build interactive dashboards.
• Distributed Computing with Apache Spark (Python and R):
• Understanding the architecture and components of Apache Spark.
• Implementing Spark applications using PySpark (Python) and SparkR (R).
• Performing distributed data processing and analysis.
• Understanding how to implement Spark SQL.
• Data Cleaning and Feature Engineering for Big Data:
• Handling missing data and outliers in large datasets.
• Implementing data transformation and normalization techniques.
• Performing feature engineering for machine learning on big data.
• Understanding how to implement feature selection.
• Machine Learning on Big Data:
• Applying machine learning algorithms to large datasets using Spark MLlib.
• Implementing distributed machine learning models.
• Evaluating model performance on big data.
• Understanding how to implement hyperparameter tuning on distributed systems.
• Data Visualization and Communication for Big Data:
• Creating interactive dashboards and visualizations for big data.
• Communicating insights effectively to stakeholders.
• Utilizing cloud-based visualization tools.
• Understanding how to visualize high dimensional data.
• Ethical Considerations and Real-World Applications:
• Understanding the ethical implications of big data analytics.
• Addressing data privacy and security concerns.
• Exploring real-world applications of big data across various industries.
• Understanding the future of big data.

CERTIFICATION

• Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

• Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

• Airport pick up and accommodation is arranged upon request

TERMS OF PAYMENT

Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com