Data has become the world’s most important currency. This interactive, hands-on course will develop the skills needed to work with large quantities of data using Python programming language and popular Python libraries, deriving valuable business insights from it using compelling visual representations such as graphs, charts, or maps. Visualisation skills lie at the heart of analytics, allowing you to make sense of data for teams and organisations.
COURSE LENGTH:
COURSE STRUCTURE:
- Introduction to Data Analytics
- Data Importing & Cleaning
- DataFrames & Data Manipulation
- Joining Data & Data Preparation
- Data Visualisation With Python
- Statistical Data Exploration
- Introduction to Modelling: Machine Learning Basics
- Preparing the Final Project
STUDY OPTIONS:
Part Time
1 hour live online evening class per week over 8 weeks. Plus 32 hours of online learning.
SUMMARY:
This certificate course will equip you to work with large volumes of data using Python programming language. You will learn the core concepts of data extraction, manipulation, and visualisation and understand how to connect insights generated by data analytics to provide valuable information from various sources, using libraries such as pandas, NumPy, matplotlib, and seaborn.
You will learn about the CRoss Industry Standard Process for Data Mining, or CRISP-DM – a process model that is the basis of data science – and in particular the phases of data understanding and data preparation. You will learn all the important aspects of extracting and preparing your data, regardless of where it originates, and explore how Python is used to find meaning and insights in this data, then present them in a visual way.
An important feature of this course is that you will be given access to self-guided learning on the DataCamp platform, a browser-based data science learning tool used by many of the world’s biggest companies and institutions. After each live lecture, you will go on to further explore the concepts through DataCamp topics, practical demonstrations, and exercises. This hands-on practice of the techniques learned will help to cement your newly acquired skills.
CAREER OPPORTUNITIES:
It’s predicted that there will be 181 zettabytes of data created worldwide by 2025. For many organisations, extracting data insights that can support and improve decision making is a big challenge. Demand for all types of analytics specialists continues to increase as more companies recognise the value of data for business growth. The skills learned on this course will benefit professionals across many different fields, including human resources, finance, sales, manufacturing, healthcare, marketing, and education. Data analysis itself is a career path that offers excellent progression and salary expectations.
ASSESSMENT AND CERTIFICATION
Your progress through the course will be marked by milestones that are reviewed and evaluated by the instructor, who will provide you with feedback. Your formal, summative assessment is through a final project showcasing your newly acquired skills in importing, cleaning, analysing, and visualising a dataset. You can use any dataset that is relevant to your work or a personal interest, as long as it does not contain personal information. Evaluation is based on the quality of data manipulation and visualisation, as well as your ability to apply the concepts covered in the course to real-world scenarios.
Your certificate will be issued electronically on a secure platform, with a link that you can share with employers and others wishing to verify your credentials. You’ll also be able to add the certification to your LinkedIn profile to demonstrate your achievement to your network as well as recruiters and potential employers searching for individuals with your skills and experience.
This course is not on the National Framework of Qualifications.
LEARNER PROFILE:
This course would suit any professional who needs to manipulate and visualise large amounts of data as part of their role - regardless of industry, sector, or department. It is also ideal for someone carving out a career in data science or data analysis. It is important to note that Python programming language is not taught during the course, so you should have previously taken a course such as our Professional Certificate in Python Programming, or similar, or have solid practical experience using Python. There is a large self-guided portion to this course – you will be expected to attend eight hours of live online lectures and complete 32 hours of online learning on the DataCamp platform, plus time for exercises and assignments.
