Data Science

Part Time 26 Weeks Online

What will I learn?

Module 1: Introduction to Programming. Learn the foundations of programming & how to code in Python. Write a simple in Python

Module 2: Programming for Data Analytics. Understand the data analysis pipeline, review the data science foundations using probability, statistics & basic data analysis, & learn classic. Create a predictive model with a given dataset

*Module 3: * Infrastructure & SQL. Learn how to use Linux/Bash & Docker, review SQL & relational databases. Create & query a relational database on Linux using Docker

Module 4: Statistics. Basic statistics lays the foundation for ML & Advanced Data Analysis. In this module we review basic statistics concepts, such as probabilities, central tendency measures & charts & graphs. Use statistical methods to analyse datasets using Jupyter notebooks

*Module 5: * Machine Learning. Learn the differences between supervised & unsupervised machine learning methods, & the different families of algorithms within each group (e.g. regression, classification, clustering). Create a predictive model for a given labelled dataset

Module 6: Advanced Data Analytics. Learn more advanced methods which deal with data types that are more complex than tables of numbers (e.g. text, geospatial data, time-series, AB testing). In this module, we will cover specific methods that apply to these types of data, as well as how to pre-process them and visualise them. Use ADA methods to analyse complex datasets

Module 7: Project Phase. Apply the knowledge gathered in the previous modules to a real use case, implementing a DA project, end-to-end. Learn how to work collaboratively & build a portfolio. Propose a problem & solve it using an ADA method. Cover all stages of the DA lifecycle in both an individual & collaborative project

*Module 8: * Career Prep. Prepare students for job interviews through logical puzzles & data challenges. Career coaching

Syllabus

Thinking about kickstarting a career in data science?Data analysis is the process of inspecting, cleansing, transforming and modelling data, using methods from statistics and database systems to discover useful information, validate conclusions, and support decision-making across domains.

What are the requirements?

No prerequisites required for this course.

Knoma's take

We love CodeOp's passion for change, and their tight-knit community for their coding, data and product courses. Their learners can benefit from their community before their course through to long after they graduate. They offer courses exclusively for women, non-binary folks, transgender folks and those transgender history, and intersex folks.

CodeOp

CodeOp is an international tech school headquartered in Barcelona, but with a campus in London. CodeOp is comprised of an international team that is passionate about doing meaningful work at the intersection of tech and education. We're changing the face of tech through our in-person and live-online bootcamps in Full Stack Development, Data Analytics and Product Managemen...
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£425 / month

£5100 interest free loan from Knoma over 12 months

Key skills

Use virtualized Linux applications with Docker Learn basic notions of programming in Python Query data using SQL and NoSQL approaches Apply common machine learning algorithms Delve into AB testing NLP and GeoSpatial Analysis
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