Data Analytics with Python: introduction
Time: 10:00 - 17:30
Location: KS - Keeley Street
This course is FREE if a) you live in London and your job is at risk of redundancy or b) you are either on Jobseekers' Allowance (JSA) or Employment & Support Allowance(ESA) or c) you receive other state benefits (including Universal Credit). For more information click here
This course takes place in the classroom, please follow this link to find out what we are doing to keep you safe: Staying COVID-19 secure at City Lit
Course Code: CADS04
Please choose a course date
Duration: 2 sessions (over 2 weeks)
What is the course about?
This course is concerned with the role of Python in the Data Analysis process. We will explore how to import data sets and use Python libraries for analysis and visualisation. Using the tools provided by the Anaconda package manager we will use more advanced development environments designed specifically for Data Science.
What will we cover?
• What Data Science encompasses
• The Data Analyst’s workflow
• How to get the tools needed
• Import and analyse data using the Numpy and Pandas libraries
• Create 2D plots of our analysis using the Matplotlib library.
What will I achieve?
By the end of this course you should be able to...
• Import data to manipulate in Python
• Use Python libraries such as Numpy and Pandas to analyse and manipulate data
• Use the Python Matplotlib library for data visualisation.
What level is the course and do I need any particular skills?
You will have completed the Introduction to Python course at the College or equivalent. If self-taught you will need to be able to:
• Use print to give the user instructions
• Get input from a user using input
• Create variables and collect and store data of different data types
• Use the if and elif for selection
• Use for and while loops
You should also be able to follow spoken instructions, read written instructions and information, and discuss work with your tutor in English.
How will I be taught, and will there be any work outside the class?
There will be some theoretical underpinning to the course, but it is nearly all practical, through Teacher demonstration and practical programming and problem solving activities. There is no official work set outside the class but it is a good idea to practise the skills you have learnt to reinforce classroom learning.
Are there any other costs? Is there anything I need to bring?
Computers are provided for each student with all the necessary software installed. All the software used on the course is free to download and use and your tutor will recommend where to find this software for home use. Unfortunately due to the range of hardware and software used by students at home, the College is unable to provide advice on installation issues.
If you wish to copy the programs you produce on the course please bring a USB key or have access to a cloud service such as Google Drive or Dropbox. A pen and notepad for note taking is also advised.
When I've finished, what course can I do next?
Data analysis with Power BI, Excel analysing data (satge 1 & 2) Introduction to DAX: data analysis expression for Power BI, Advanced Python, Introduction to R programming.
Amit is an entrepreneur currently working on an immersive content technology concept within the Launchpad incubator at Falmouth university. He completed a Masters in Advanced Computing with a specialisation in Data Analytics from Birbeck College, University of London where his final thesis investigated the use of NLP and machine learning on tweets to predict the price of Bitcoin. Amit also holds a Masters in Electronic and Information Engineering from Imperial College London. Prior to joining Launchpad, he has worked as a Data Analyst, Business Analyst and Project Manager at various startups, in the social sector, and within fintech and eCommerce spaces. Earlier in his career, he taught English in Brazil to students of all ages and spent a number of years working in East Africa as a Business Developer within manufacturing, trading and online retail spaces. His experience includes programming (Python, R, and C#), databases (relational databases and graph), an in-depth understanding of using various machine learning and predictive modeling techniques, and the use of data visualisation tools such as Looker and Tableau.
Please note: We reserve the right to change our tutors from those advertised. This happens rarely, but if it does, we are unable to refund fees due to this. Our tutors may have different teaching styles; however we guarantee a consistent quality of teaching in all our courses.