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Data Analysis Intensive

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Syllabus:

Python

SQL

Tableau

Projects

2 COURSE FORMATS:

CLASSROOM – 3 Weeks @ Monument, London, Mon to Fri (15 sessions), 6:30pm to 8:30pm

Courses currently on hold

REMOTE – 3 Weeks, via Live Video Feed, Mon to Fri (15 sessions), 6:30pm to 8:30pm

Join our Remote Course on 20th July 2020

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By the end of this course:

You will design Tableau dashboards, moving from start to finish through the Data Analysis pipeline.

Select, create and update data stored in a database with SQL. Learn the core libraries of Python including Pandas for analysing data in various formats. Prepare beautiful visualisations in Tableau.

All of which add value to your employer. 

Or try our 1 Day Weekend Tableau Course

8 Hour Saturday Course – from £225 + VAT

Info

Example Tableau dashboards produced in the class, looking at 1) a UK bank’s client distribution, 2) profit margins amongst competing Australian companies.

Our Teaching:

We firmly believe in classroom-based study versus online, pre-recorded content, because it ensures your teacher is always on-hand to help you with the challenges you encounter.

We also teach through projects of your choice, allowing you to choose the direction of your learning at a pace that suits you.

Our Teachers:

Our teachers are Data Analysts and Data Scientists who exhibit a real passion for this field.

They come with years of commercial and academic teaching experience –

Meet Stefan Marwah

Stefan is a Step Function Data Analysis teacher who works in London’s finance sector as a Quantitative Analyst. Stefan has used Python for 6 years and has taught both the Step Function Data Analysis course and Introduction to Python course on several occasions.

 

 

Stefan’s extensive knowledge of Python, SQL and Tableau ensures strong outcomes for our students.

Student Review:

 

“I had a very positive experience as a student of Step Function’s Data Analytics Intensive course. I wanted a career changed so I joined the course to learn the needed skills to transition into a new career. It was challenging but was taught by a very knowledgeable instructor who went through every step in detail. I did learn a lot at SF and left with the skills needed to teach myself new programming languages. This is an incredibly useful skill-set to have. Stefan was a fantastic instructor and very invested in the success of the class. He was very informative and supportive.”

 

FAWAZ POPOOLA (NHS) – August 2018 Course

 

“I wanted to drop you a note to tell you how pleased I was with the content and the teaching. Both Stefan and the curriculum were fantastic. Thank you!”

 

YOANA MATEEVA – (TRACTABLE – AI for accident recovery) – January 2019 Course

Data Analysis Intensive Course Syllabus

WEEK 1 - Data Analysis Fundamentals with Python

Introduction

  • From database to knowledge: the data analysis pipeline
  • Future-proofing your data: the three “normal forms” of database design
  • Setting up your environment
  • Syntax and Style
  • Procedural vs. declarative programming: Python vs. SQL

 

Python

  • Fundamental structures and types
  • Logic and Control flow
  • Exercises
  • Structuring your code
  • Functions
  • Core libraries
  • Working with APIs
WEEK 2 - Pandas and NumPy, SQL

Python

  • Grouping and Aggregating
  • Reading and Writing Data in Pandas
  • Cleaning Data in Pandas
  • Data Visualisation
  • Utilising NumPy

 

SQL Introduction

  • Selecting, creating and updating data
  • Introduction to ER Diagrams
  • Data Types in SQL
  • DDL – (Data Definition Language)
  • Installing MySQL
  • Data Manipulation Language
WEEK 3 - SQL and Tableau

SQL

  • Handling the messy reality of real-world data
  • Complex join expressions
  • Aggregate Functions
  • Joins
  • Subqueries
  • Views
  • Python & MySQL
  • Connecting a Postgresql Database

 

Tableau Introduction

  • Tableau Installation
  • 10 Minute Plot
  • Connecting to a CSV file
  • Calculation fields and Formatting
  • Time Series
  • Aggregation
  • Filters

 

Advanced Tableau

  • Scatterplots
  • Dual Axis Chart
  • Joining v Blending Data
  • Geographical roles
  • Bins and histograms
  • Tree Charts

 

Bonus Material

  • Clustering
  • Cross Data Source Joins
  • Animations

Please note that the details of this Introduction to Python Course syllabus are accurate at the time of printing. There may be some variation in the final syllabus that is taught.

Step Function, August 2019

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