01
Data Workflow
Understand how data is collected, processed, and analysed
Courses Data Processing with Python
Course Course
Humain Academy
Data Processing with Python
Go from basic Python to analysing data, building insights, and preparing datasets for machine learning in 6 weeks.
- Duration
- 45 total learning hours over 6 weeks
- Level
- Intermediate, Basic knowledge of Python programming and familiarity with basic programming concepts
- Format
- 12 live online lectures + Q&A clinics + self-study + assessments
- Delivery
- Online only, live video conferencing
About the Course
Data Processing with Python
This course introduces you to data science using Python, focusing on how to work with real-world datasets and extract meaningful insights.
You will learn how to manipulate data using powerful libraries like NumPy and pandas, clean and prepare datasets, and explore patterns through visualisation and statistical analysis.
By the end of the course, you will be able to analyse data, communicate insights effectively, and build simple machine learning models.
Prerequisites
Who is this course for?
Open to all individuals aged 16+ with a basic knowledge of Python programming and familiarity with basic programming concepts
Python Learners
Individuals ready to apply Python to real-world data
Aspiring Data Analysts
Those interested in data-driven roles
Future Data Scientists
Learners preparing for machine learning
Learning Outcomes
Skills you’ll demonstrate
02
Tools & Ecosystem
Explore key libraries used in data science
03
NumPy Arrays
Perform efficient numerical computations
04
pandas DataFrames:
Structure, filter, and transform datasets
05
Handling Missing Data
Clean and prepare real-world datasets
06
Data Quality
Remove duplicates and manage outliers
07
Exploratory Data Analysis (EDA)
Identify patterns and trends
08
Visualisation
Create charts using Matplotlib and Seaborn
09
Statistical Concepts
Work with distributions and correlations
10
Hypothesis Testing
Draw meaningful conclusions from data
11
Feature Engineering
Prepare data for modelling
12
Intro to ML Models
Apply basic regression and classification
13
Data Storytelling
Present findings clearly
14
Dashboards & Reports:
Communicate insights effectively
Curriculum Modules
1 Session 1 Data science landscape
Understand roles, tools, and workflows in data science
2 Session 2 NumPy fundamentals
Work with arrays and numerical operations
3 Session 3 pandas (Part 1)
Use DataFrames, indexing, and slicing
4 Session 4 pandas (Part 2)
Perform grouping, merging, and reshaping
5 Session 5 Data cleaning
Handle missing values, duplicates, and outliers
6 Session 6 Exploratory data analysis
Analyse data to identify patterns and insights
7 Session 7 Data visualisation (Part 1)
Create visualisations using Matplotlib
8 Session 8 Data visualisation (Part 2)
Use Seaborn and improve data storytelling
9 Session 9 Statistics
Work with distributions, correlation, and hypothesis testing
10 Session 10 Feature engineering
Prepare datasets for machine learning
11 Session 11 Intro to ML
Apply regression and classification models
12 Session 12 Communicating insights
Build dashboards and present findings
FAQs
Do I need prior experience in data science?
No. This course is designed for learners with basic Python knowledge who want to start working with data.
Will I work with real datasets?
Yes. You will complete hands-on exercises and analyse real-world datasets throughout the course.
What tools will I use?
You’ll use Python with key libraries such as NumPy, pandas, Matplotlib, and Seaborn.
Is this course suitable before Machine Learning?
Yes. This course is the ideal step before moving into Machine Learning, as it teaches how to prepare and analyse data.
Turn Data into Insights with Python
Enroll now or request information about upcoming sessions.
Data Processing with Python
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