Learn Big Data Analysis With Python Training Course in Singapore
Master data-driven decision-making with our Big Data Analysis with Python Training Course in Singapore. Learn data processing, visualization, and predictive analytics to boost your career opportunities.
Schedule
- Days: 2 Days
- Duration: 14 Hours
- Timings: 9:30 AM - 5:30 PM
- 10 Anson Road, 26-08A International Plaza, Singapore 079903
Why Choose Us
- Expert Local Trainers
- Hands-on Training by experts
- Certificate of Achievement
Who Should Attend Big Data Analysis With Python Course
Big Data Analysis With Python Training Course is ideal for those who want to become data analyst.
Business professionals
Analyst
Entrepreneur
Training Professionals
Student
Course Completion Requirements
Minimum 75% attendance is required in order to complete the course and receive the course completion certificate
Above 16 years old
High School Level English
Basic internet & computer operation skills
Big Data Analysis With Python
This course is designed for Python Developers, Data Analysts, and Data Scientists
Learn how to handle large volumes of data and turn them into clear, interactive insights using Spark and Python. This course helps you make sense of big data and present it in a way that’s both engaging and easy to understand.
What will you learn?
By the end of this course, you’ll be able to bootstrap your own Python environment, process large files, and manipulate data to generate statistics, metrics, and graphs
Learning Objectives
- Use Python to read and transform data into different formats
- Generate basic statistics and metrics using data on the disk
- Work with computing tasks distributed over a cluster
- Convert data from various sources into storage or querying formats
- Prepare data for statistical analysis, visualization, and machine learning
- Present data in the form of effective visuals
Unsure if this course is suitable for you? Take this Quick test to help you decide.
Big Data Analysis With Python Course Outlines
Lesson 1: The Python Data Science Stack
- Python Libraries and Packages
- Using Pandas
- Data Type Conversion
- Aggregation and Grouping
- Exporting Data from Pandas
- Visualization with Pandas
Lesson 2: Statistical Visualizations
- Types of Graphs and When to Use Them
- Components of a Graph
- Which Tool Should Be Used?
- Types of Graphs
- Pandas Data Frames and Grouped Data
- Changing Plot Design: Modifying Graph Components
- Exporting Graphs
Lesson 3: Working With Big Data Frameworks
- Hadoop
- Spark
- Writing Parquet Files
- Handling Unstructured Data
Lesson 4: Diving Deeper With Spark
- Getting Started with Spark DataFrames
- Writing Output from Spark DataFrames
- Exploring Spark DataFrames
- Data Manipulation with Spark DataFrames
- Graphs in Spark
Lesson 5: Handling Missing Values And Correlation Analysis
- Setting up the Jupyter Notebook
- Missing Values
- Handling Missing Values in Spark DataFrames
- Correlation
Lesson 6: Exploratory Data Analysis
- Defining a Business Problem
- Translating a Business Problem into Measurable Metrics and Exploratory Data Analysis (EDA)
- Structured Approach to the Data Science Project Life Cycle
Lesson 7: Reproducibility In Big Data Analysis
- Reproducibility with Jupyter Notebooks
- Gathering Data in a Reproducible Way
- Code Practices and Standards
- Avoiding Repetition
Lesson 8: Creating A Full Analysis Report
- Reading Data in Spark from Different Data Sources
- SQL Operations on a Spark DataFrame
- Generating Statistical Measurements
Frequently Asked Questions (FAQs)
Who is this course designed for?
The course is designed for aspiring data analysts and professionals such as IT professionals, data analysts, data scientists, training professionals, and students. It’s especially suited for those looking to master big data processing using Spark and Python.
What prerequisites do I need before enrolling?
You should be at least 16 years old, possess high-school–level English proficiency, and have basic internet and computer skills.
What is the duration and format of the course?
The training spans 2 days, totaling 14 hours.
What will I learn by the end of the course?
A minimum of 75% attendance is required to complete the course and receive the course completion certificate
What will I learn by the end of the course?
You’ll learn how to set up your Python environment, process large datasets, manipulate data to derive statistics and visualizations, and deliver interactive insights using Spark and Python.