Introduction

Python has been one of the most adaptable, and robust open-source languages that are easy to learn and uses powerful libraries for data manipulation and analysis. For many years now, Python has been used in scientific computing and mathematical domains such as physics, finance, oil and gas, and signal processing. This Big Data Analytics with Python course provides a complete overview of data analysis techniques using Python. The Big Data Analytics with Python course teaches you to master the concepts of Python programming. Through this training, you will gain knowledge of the essential tools of Data Analytics with Python

Programme Curriculum

Training on Big Data analytics using Python

Day 1: Introduction to Big Data and Python

Morning:

Welcome and Introduction to the Course
Overview of Big Data and its Challenges
Introduction to Python for Data Analytics
Setting up Python Environment (Anaconda, Jupyter Notebook)

Afternoon:

Basic Python Programming Concepts (Variables, Data Types, Loops, Functions)
Introduction to Pandas (DataFrames and Series)

Day 2: Data Manipulation and Preprocessing

Morning:

Data Cleaning and Handling Missing Values
Data Transformation (e.g., filtering, sorting, merging)
Data Visualization with Matplotlib and Seaborn

Afternoon:

Introduction to NumPy for Numerical Operations
Exploratory Data Analysis (EDA)
Case Study: Exploring a Real-world Dataset

Day 3: Big Data Tools and Distributed Computing

Morning:

Introduction to Big Data Technologies (Hadoop, Spark)
Overview of HDFS (Hadoop Distributed File System)
Setting up a Hadoop/Spark Cluster (Local or Cloud)

Afternoon:

Introduction to PySpark
Working with RDDs (Resilient Distributed Datasets)
Basic Data Processing with PySpark

Day 4: Advanced Data Analytics with Python

Morning:

Machine Learning with Scikit-Learn
Model Training and Evaluation
Feature Engineering

Afternoon:

Introduction to Deep Learning with TensorFlow/Keras
Neural Networks and Deep Learning Concepts
Hands-on Deep Learning Exercise

Day 5: Big Data Analytics and Conclusion

Morning:

Large-scale Data Processing with PySpark
Building Data Pipelines
Real-time Data Processing (Optional)

Afternoon:

Final Project: Applying Big Data Analytics on a Real Dataset
Presentation of Projects
Q&A Session
Course Conclusion and Certification

Methodology

The instructor led trainings are delivered using a blended learning approach and comprises of presentations, guided sessions of practical exercise, web-based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields.

Key Notes

i. The participant must be conversant with English.

ii. Upon completion of training the participant will be issued with an Authorized Training Certificate

iii. Course duration is flexible and the contents can be modified to fit any number of days.

iv. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

v. One-year post-training support Consultation and Coaching provided after the course.

vi. Payment should be done at least a week before commence of the training, to Fineskill Training Center account, as indicated in the invoice so as to enable us prepare better for you

Skills & Software Covered

Python Big Data Data Analysis Data Visualization Machine Learning

Programme Fee

Duration: 5 Days

Method: Online or Physical

Online Price: $1,000

Physical Price: $1,500

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Oct 19 2026

19 Oct — 23 Oct 2026

💻 Online / Virtual session

Online $1,000