DebKR

To the Stars

Personalised Training Plan

Business Analytics: PTP and Syllabus

Business Analytics: PTP and Syllabus

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analyticsBusiness Analytics: personalised training plan

Key Learning Objectives
Understand data-rich business environments and their commercial drivers (incl. how they differ from trad. businesses)
Understand and apply business metrics best practice (setting, measuring, reporting, decision-making)
Select and use relevant data tools to solve business problems (competitiveness, profitability, cash flow, marketing)
Understand and apply critical business metrics for internet marketing / direct-response marketing businesses
Apply data analysis best practice (framing the problem, developing robust predictive models, generating insights and value from data, visualising/communicating data and insights) [Read more…] about Business Analytics: PTP and Syllabus

Programming in Python: First Steps

Programming in Python: First Steps

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python0PTP 1. Programming Stream / B. Python (beginner)

PTP Outcomes:
Familiarise myself with Python language and ecosystem
Be able to do simple coding exercises
Gain an insight into Python’s use in data science, data manipulation and visualisation
Familiarise myself with relevant data analysis packages/libraries

Initial thoughts
As mentioned in my Introduction to Data Science post, I’ve researched and set myself a Personalised Training Plan based on the knowledge/skills I’ll need to learn and develop if I’m to pivot my career away from finance/accountancy and towards data/analytics. As first steps in the Programming and Data Science streams, I’ve signed up for two specialisations at Coursera.org (links here and here). [Read more…] about Programming in Python: First Steps

Introduction to Data Science

Introduction to Data Science

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launchPTP 5. Data Science Stream / A. Introduction to data science

PTP Outcomes:
Learn about the history of data science, where it’s come from, where it’s going to
Get an overview of the main principles, methods and applications of data science
Understand how data scientists develop insights from raw data, and how they present those insights to others
Become familiar with the most important tools, languages, platforms being used by data scientists
Learn about the fundamentals of data engineering

Some thoughts before I being
My Personalised Training Plan has been set after reasonably extensive research online, taking account of topics covered by various online and offline schools/courses, the advice of Analytics Vidhya and Ajit Jaokar on how to move into a data science career, as well as a review of key skills required by data scientists based on current jobs advertised online (e.g. on LinkedIn). [Read more…] about Introduction to Data Science

Diving Into Data: Course Listing (work in progress)

Diving Into Data: Course Listing (work in progress)

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coursesStanford Engineering Everywhere
URL: https://see.stanford.edu/Course

Computer Science/Programming: Programming Methodology; Programming Abstractions; Programming Paradigms

Artificial Intelligence: Introduction to Robotics; Machine Learning [Read more…] about Diving Into Data: Course Listing (work in progress)

Diving Into Data: Personalised Training Plan (work in progress)

Diving Into Data: Personalised Training Plan (work in progress)

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training-planBelow is my personalised training plan to move into a career in Data/Analytics with Machine Learning, with specific reference to consumer-direct/e-commerce business. To be implemented throughout March- November 2016.

Areas to cover

Mathematics: Linear algebra, Multivariate calculus

Probability and Statistics: Inferential stats, Descriptive stats, Regression analysis (linear, logistic), Cluster analysis, Classification and regression tree model (CART), Hypothesis testing, Decision trees, Predictive modelling/forecasting [Read more…] about Diving Into Data: Personalised Training Plan (work in progress)