Python Essentials for Data Science: 1 Day Session in London
Schedule
Tue, 16 Dec, 2025 at 09:00 am to Wed, 17 Jun, 2026 at 05:00 pm
UTC+00:00Location
For more information on venue address, reach out to "[email protected]" | London, EN
About this Event
Bring your team and save
1. Groups of three or more receive a 10% discount
2. Organizations hosting an in-house session with 10+ participants enjoy a 15% discount.
Duration: 1 Full Day (9:00 AM – 5:00 PM)
Delivery Mode: Classroom (In-Person)
Language: English
Credits: 8 PDUs / Training Hours
Certification: Course Completion Certificate
Refreshments: Lunch, beverages, and light snacks included
Course Overview:
The Python for Data Analyst course helps you harness the power of Python for statistical analysis, reporting, and automation. Designed for analysts and business professionals, it introduces tools like Pandas for data manipulation, Matplotlib for visualization, and techniques for integrating with Excel or databases. This hands-on course transforms how you automate reporting, create dashboards, and derive business insights from data.
Learning Objectives:
By the end of this course, you will:
- Manipulate and analyze data efficiently using Pandas
- Visualize key business metrics with Matplotlib
- Apply statistical methods to find trends and patterns
- Automate repetitive data tasks using Python scripts
- Integrate Python outputs into Excel and database environments
- Build ready-to-execute analysis workflows for business use
Target Audience:
Data analysts, business analysts, finance professionals, and researchers.
Why is it the Right Fit for You?
If you're involved in data-driven decision-making, this course empowers you to work smarter using Python. With a focus on real-world applications, we teach you practical skills — from transforming raw data to automating reports — that help optimize business processes. Our hands-on format ensures you learn by doing, while our industry expert trainers guide you through common challenges and scenarios encountered in business analytics. This course bridges the gap between Excel and advanced analytics tools, helping you elevate your skills and value as an analyst.
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Do you want to equip your team with advanced data analytics skills?
We offer in-house Python for Data Analyst training that can be customized to your business processes, data formats, and reporting needs. Curious how Python can streamline your team's workflows and insights? Let us build a tailor-made learning experience for your organization.
📧 Contact us today to schedule a customized in-house session: [email protected]
Agenda
Module 1: Introduction to Python for Analytics
Info: • Understanding Python in the analytics ecosystem
• Setting up Jupyter Notebook or VS Code
• Overview of key libraries for analysis
• Activity
Module 2: Data Manipulation with Pandas
Info: • Working with DataFrame and Series
• Importing and exporting data from CSV, Excel, SQL
• Filtering, sorting, and merging data
• Activity
Module 3: Data Cleaning Techniques
Info: • Handling missing values and duplicates
• Text and date transformations
• Data type conversions and standardization
• Activity
Module 4: Data Visualization with Matplotlib
Info: • Creating line, bar, pie, and scatter plots
• Customizing plot styles, labels, and legends
• Comparing datasets visually
• Activity
Module 5: Statistical Analysis in Python
Info: • Descriptive statistics and summary functions
• Correlation and distribution analysis
• Using SciPy for hypothesis testing
• Case Study
Module 6: Excel and Database Integration
Info: • Reading and writing Excel files
• Connecting to SQL databases
• Automating workflows with Python scripts
• Activity
Module 7: Automating Reports
Info: • Generating daily/weekly reports with code
• Exporting visuals and data summaries
• Emailing or saving outputs automatically
• Activity
Module 8: Mini Project
Info: • Clean, analyze, and visualize a real dataset
• Create a Python-based automated report
• Present insights and code
• Activity
Where is it happening?
For more information on venue address, reach out to "[email protected]", Ph No: +1 469 666 9332, London, United KingdomEvent Location & Nearby Stays:
GBP 536.99 to GBP 704.92
