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Python for Data Analysis

Take your data skills to the next level with Python for Data Analysis. This short course will introduce you to the essential tools and techniques used in data science, from handling large datasets with Pandas to performing advanced visualisations with Matplotlib and Seaborn. Whether you’re new to Python or looking to refine your analytical skills, you’ll gain practical experience working with real-world data, making sense of complex datasets, and applying statistical methods to uncover insights.

Why Itonlinelearning?

  • Hands on, scenario based learning
  • Job ready GitHub portfolio activities

Take Your Data Analysis Skills to the Next Level!

This short course is just the beginning of your journey. Combine it with other key modules by earning the Data Analysis Diploma, a comprehensive programme designed to turn you into a career ready data analysis.

Unlock access to expert tutors, practical projects, and a job-ready portfolio

What’s included

In your Python for Data Analysis short course

This course provides a structured, practical, and job-focused approach to mastering Python for data analysis. Here’s what you’ll gain:

  • Fundamentals of Data Analysis: Work with numerical data, indexing, sorting, and reshaping datasets.
  • Essential Python Libraries: Learn to manipulate data with NumPy and Pandas for efficient analysis.
  • Data Cleaning & Preprocessing: Prepare and structure raw data for meaningful insights.
  • Time Series & Statistical Analysis: Explore forecasting, trends, and statistical modelling with Statsmodels and SciPy.
  • Hands-On Projects: Apply your skills to real-world datasets, reinforcing key concepts in data science.

Create a portfolio that showcases your skills to impress hiring managers

Build a professional portfolio that showcases your data analysis skills and practical experience, exactly what employers value. By featuring real-world projects on your GitHub, you’ll demonstrate your ability to work with data effectively, solve analytical challenges, and showcase the expertise and problem-solving abilities that hiring managers seek.

Meet your expert tutors

Our career-focused curriculum, 1:1 calls with your tutors, and hands-on projects, will help you create a job-ready data analysis portfolio that will get you hired in no time.

Your tutors will help you:

  • Personalised feedback: Your tutor will work closely with you to understand your learning style, strengths, and areas for improvement, tailoring their approach to maximise your growth. 

  • Real-time support: Stuck on a tricky problem? Your tutor will dive into your problem with you, offering real-time feedback and helping you develop best practices. 

  • Motivation and Accountability: Your tutor will check in regularly, helping you stay focused, motivated, and ensure a thorough understanding of the material. They provide detailed walkthroughs, past papers.

  • Career Coaching: As you progress, your tutor and recruitment advisor will help you build a standout portfolio, prepare for technical interviews, and navigate the job market with confidence. 

Python for Data Analysis
Frequently Asked Questions

What about practical experience?

During this course, you will have access to over practical exercises or projects that will help you implement your newly acquired Python for Data Analysis skills.

What finance options do you offer?

We offer finance through our third-party finance partner Premium Credit where you can spread the cost of your study package and exams over affordable monthly payments. This is the preferred option for our students not paying in full. As an alternative where students do not qualify for finance, we offer monthly spread payments in-house (ITOL Finance) which are interest-free and cover the cost of the course component only. ITOL Finance therefore does not finance the cost of exams. You can, however, contact the exam booking team at any time and pay for exams as you need them.

Can you tailor a study package for me?

Yes, we can tailor a study package for you based on your experience level and taking into consideration studies you have already completed.