# Course 03: Data Science
import pandas as pd
import numpy as np
def analyze_data(dataset):
    return "Insights Discovered"

Data Science
with Python

Transform data into insights using Python's scientific computing ecosystem through practical training in analysis, visualization, and machine learning libraries. Master the complete data science pipeline.

€750
Course Fee
10
Weeks
40
Hours
Back to Home Enroll Now
Data science with Python learning environment

Course Overview

What You'll Master

This advanced course covers NumPy arrays, Pandas DataFrames, and Matplotlib visualizations while developing analytical workflows. Students learn to perform statistical analysis, implement machine learning algorithms with Scikit-learn, and create interactive visualizations with Plotly.

Data Analysis & Visualization

NumPy, Pandas, Matplotlib, and Plotly for comprehensive analysis

Machine Learning

Scikit-learn algorithms for classification, regression, and clustering

Web Scraping & APIs

BeautifulSoup data extraction and API integration techniques

Jupyter Notebooks

Best practices for interactive analysis and presentation

# Data analysis workflow
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
# Load and explore data
df = pd.read_csv('dataset.csv')
print(df.describe())
# Machine learning pipeline
X_train, X_test, y_train, y_test = train_test_split(X, y)
model.fit(X_train, y_train)
print(f"Accuracy: {model.score(X_test, y_test)}")

Career Opportunities

Data science skills are among the most sought-after in today's job market. Our graduates have successfully transitioned into data analyst, machine learning engineer, and business intelligence specialist roles.

Analyst Positions

Data analyst, business intelligence specialist, research analyst roles

75%

Average salary increase for data science positions

15+

Industries seeking data science professionals

# Career transitions from September 2025
data_careers = {
    "Georgios": "Data Analyst at Banking Corp",
    "Helena": "ML Engineer at Tech Startup",
    "Michalis": "BI Specialist at Retail Chain"
}

Data Science Toolkit

Learn with the complete Python data science stack used by professionals worldwide. Our lab provides access to powerful computing resources and the latest data science libraries and tools.

Pandas & NumPy

Data manipulation and numerical computing foundations

Visualization Suite

Matplotlib, Plotly, and Seaborn for stunning visualizations

Machine Learning

Scikit-learn, TensorFlow basics, and statistical modeling

Jupyter Environment

Interactive notebooks with GPU acceleration support

# Data science stack
numpy==1.24.3
pandas==2.0.3
matplotlib==3.7.2
plotly==5.15.0
scikit-learn==1.3.0
jupyter==1.0.0
beautifulsoup4==4.12.2
requests==2.31.0
# Analysis example
import pandas as pd
df = pd.read_csv('data.csv')
insights = df.groupby('category').mean()
print(insights.head())

Data Science Methodology

Statistical Foundation

Build strong statistical foundations essential for data science work. Learn hypothesis testing, descriptive statistics, probability distributions, and correlation analysis using Python libraries.

Descriptive and inferential statistics
Hypothesis testing and p-values
Regression and correlation analysis
Probability distributions and sampling

Machine Learning Pipeline

Master the complete machine learning workflow from data preprocessing to model evaluation. Learn feature engineering, model selection, and performance optimization techniques.

Data cleaning and preprocessing techniques
Feature selection and engineering
Model training and validation strategies
Performance metrics and optimization

Perfect Candidates

This advanced course is designed for programmers with solid Python foundations who want to specialize in data science and analytics. Ideal for professionals working with data who want to unlock deeper insights.

Data Professionals

Analysts, researchers, and business professionals who work with data and want to enhance their analytical capabilities with Python.

Python Developers

Programmers with Python experience looking to pivot into data science and machine learning career paths.

STEM Graduates

Science, technology, engineering, and mathematics graduates seeking to apply their quantitative skills in data science roles.

Prerequisites

requirements = {
    "python_skills": "Intermediate to advanced level",
    "mathematics": "Basic statistics and algebra",
    "data_experience": "Some exposure to data analysis",
    "dedication": "10 weeks intensive learning"
}

Data Science Projects

Complete hands-on projects that demonstrate real-world data science applications. Build a portfolio showcasing your ability to extract insights from various types of datasets.

Sales Data Analysis

Comprehensive analysis of retail sales patterns and trends

Web Scraping Project

Extract and analyze data from websites using BeautifulSoup

Predictive Model

Machine learning model for classification or regression tasks

Interactive Dashboard

Plotly-based visualization dashboard for business insights

# Project portfolio structure
projects/
├── sales_analysis/
│ ├── data_cleaning.ipynb
│ ├── exploratory_analysis.ipynb
│ └── visualization.ipynb
├── web_scraping/
│ ├── scraper.py
│ └── analysis.ipynb
├── ml_prediction/
│ ├── model_training.ipynb
│ └── evaluation.ipynb
└── dashboard/
    ├── app.py
    └── requirements.txt

Transform Data Into Insights

Join our advanced Data Science with Python course and unlock the power of data analysis, visualization, and machine learning. Build the skills that companies in Cyprus and worldwide are seeking.

Enroll in Data Science Course Compare All Courses
€750 course fee
10 weeks advanced
ML & analytics focus
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