Data Science Course
- With Personal Coaching

Enter the world of Full-Stack Data Science through Data Analytics, Data Wrangling, Machine learning and Data Storytelling

data-science-course-growth-tribe

Data Science Skills Are In High Demand

Did You Know?

0 %

Year on year growth of data science job listings since 2019

Source: Indeed.com

Did You Know?

# 10

Ranking for top jobs in 2020

Source: Onwardsearch 2019 Salary Guide

Did You Know?

100 %

Annual AI-related Hiring Growth (2015-2019)

Source: LinkedIn Learning 2019 Report

So We Built A Course By - and for - Data Professionals

Discover the fundamentals of evidence from data.

How: by executing basic descriptive analysis using python.

Discover the fundamentals of data preparation for analysis. How: executing basic functions in SQL, pandas, and git and performing an exploratory analysis.

Discover the fundamentals of evidence from data.

How: by executing basic prescriptive analysis using python.

Discover the fundamentals of predictive models.

How: by executing the basic steps of classification models. Using: python and low code tools.

Discover the main hyperparameters of supervised learning.

How: by executing the basic steps of continuous values predictions. Using: python and low code tools.

Discover the fundamentals of unsupervised learning.

How: by executing the basic steps of clustering models. Using: python and low code tools.

Build upon the fundamentals of effective visualization of exploratory and explanatory data analysis.

Build upon the fundamentals of effective presensation of results from data analysis.

Around Tools You Will Learn To Master

data science tools growth tribe
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data science tools github
google-colab-logo
data science tools matplotlib
data science tools aws
data science tools sql
data science tools tableau
data science tools keras
data science tools numpy
data science tools docker
data science tools power bi
data science tools jupyter notebook
data science tools scikitlearn
data science tools dataiku
data science tools kubernetes
data science tools pandas
data science tools paperspace

Based On Foundational Books

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practical-statistics-for-data-scientists
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Here's The Structure Of The Program

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12 Weeks of courses and exercises

12 weeks of live courses, homework (approx. 5hrs per week), exercises, reading, videos, templates, micro-learning and engaging interactions with peers

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6x Personal Coaching Sessions

Six personalised coaching sessions with your mentor to facilitate your learning progress based on your specific needs

Build A Personal Project To Showcase

Build multiple shared projects and a final personal project by the end of the program

Growth Tribe

Lifelong Access & Support

Lifelong access to your online learning environment: review content, videos & resources and stay connected with your community of peers

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And some of your instructors 🙂

Bernardo-F-Nunes-Data-Science-Expert-Round

Bernardo F. Nunes

PhD. Business applications of Data Science and Behavioural Science.

Judit-Szaffenauer-Data-Science-Expert-Rounded

Judit Szaffenauer

Machine Learning, Business Applications of Data Analytics and Market Research.

Mauricio-Bernardo-Da-Silva-Data-Science-Expert-Rounded

Mauricio Bernardo da Silva

Data Analysis, Machine Learning

Juan-Venegas-Data-Science-Expert-Rounded

Juan Venegas

Mathematical modelling, commercial storytelling, filmmaking, coding.

Theo-Saroglou-Data-Science-Expert-Rounded

Theo Saroglou

Behavioral Economics, Game Theory, Econometric

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Google

No joke. Google will be one of your most important trainers 🙂

The Story Begins With A Personal Capability Scan

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The personal assessment will give both you and your coach a clear view of your strengths and main improvement points in the topics that are relevant to this course. We can then adapt your online learning journey to better match your goals. No one-size-fits-all learning here!

Cross-functional UX Designers are in high demand

2020 sees the emergence of cross-functional UX designers. It’s a shift from specialised designers, to generalists who also have an understanding of analytics, business, marketing, data, code, automation and persuasion. These generalists are hired faster, earn more and are more resilient.

Core UX capabilities:

  • General User Research
  • User Needs Evaluation
  • Usability Evaluation
  • Metrics and Measurements
  • Information Architecture
  • Prototyping
  • Interaction Design
  • Visual Design
  • Writing
  • Stakeholder Management
  • Professional Cooperation
  • Business and Strategy
  • Development
  • Workshop Facilitation
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Learning Experience

Here Are More Details About The Program

A Personal Capability Scan Before The Course Starts

The personal assessment will give both you and your coach a clear view of your strengths and main improvement points in the topics that are relevant to this course. We can then adapt your online learning journey to better match your goals. No one-size-fits-all learning here!

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Live Online Workshops delivered by Expert Trainers

Our online courses are hosted live to ensure real time teaching and facilitation from our experienced Data Science practitioners. Class sizes are limited to ensure you get the real-time support you need.

Immersive Group Interaction with Team Breakout Sessions

Enjoy online break-out sessions for group discussion and peer-to-peer learning, all during live classes. Participants work on real business cases and share their knowledge with the group.

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Real-Time Exercise Walkthroughs, Guidance & One-to-One Coaching

You’ll stay engaged with hands-on exercise walk-throughs, and live discussions with trainers and fellow alumni using the latest educational conferencing technologies. You’ll also have regular remote coaching sessions tailored to your specific needs.

Example of a project you'll work on

Building a prediction model to predict customer lifetime value estimations. Then creating visualisations to communicate this to an online retailer.

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Example of a project you'll work on

Building customer churn prediction models for a subscription business model using Deep Neural Networks in Google Colab. Then communicating the results to the business.

Example of a project you'll work on

Using a neural network model to build a lead scoring model in order to predict the probability that a customer is a qualified lead for a demo. Applying supervised learning to past data containing demographics and behavioural information of users in the last 90 days.

prediction model
image-recognition-clustering

Example of a project you'll work on

Using Convolutional Neural Networks to build image recognition models. In this example the student uncovered similarities in images through hierarchical clustering. This allowed to uncover trends for a customer which would have required many hours of manual work.

Get your hands dirty with key tools of the industry

Use the latest and most important tools. We’re  addicted to tools and want to share that healthy addiction with you.

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Learn at your own pace with brand new self-study tracks

These brand new study tracks allow you to apply your learnings, expand your knowledge and up your skills at your own pace.

Get certified

Graduate with a Growth Tribe certification of competence. You’ll also receive a virtual certificate which alumni add to their Linkedin profile.

growth-tribe-certification
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Lifelong access to content & alumni community support

You’ll receive lifelong access to the course material through our online learning environment as well as lifelong support from our trainers & your peers through our exclusive online communities.

See What An Online Growth Tribe Course Feels Like

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Detailed Course Curriculum

Before the course starts

We’ll run a complete capability scan in these key capability areas:

  • Mindset & Professional skills
  • Data Science Role-Specific Capabilities (e.g. Data Analytics, Data Wrangling, Machine learning and Data Storytelling…)
  • Baseline of outcomes (success KPIs we define for the program)

Week 1 - Practical Statistics For Data Science

What we’ll be doing:

  • Discover the fundamentals of evidential science by executing basic functions in Python 
  • How: by executing basic descriptive analysis using python
  • Build means comparisons tests between groups
  • Build basic summaries of statistics and simple visuals to explore a data set
  • Define the workflow, tools, and approaches data scientists use to analyze data
  • Apply the Data Science Workflow to solve a task

Tools we’ll be using

  • Google Colab
  • numpy
  • pandas
  • matplotlib

Week 2 - Data Wrangling

  • What we’ll be doing:

    • Discover the fundamentals of evidential science by executing basic functions in Python 
    • How: by executing basic descriptive analysis using python
    • Build means comparisons tests between groups
    • Build basic summaries of statistics and simple visuals to explore a data set
    • Define the workflow, tools, and approaches data scientists use to analyze data
    • Apply the Data Science Workflow to solve a task

    Tools we’ll be using

    • Google Colab
    • numpy
    • pandas
    • matplotlib

Week 3 - Project & T-shaping

Focus on key capabilities to strengthen your T-shape Depending on your skills assessment these could be:

  • Data Analytics
  • Data Wrangling
  • Machine Learning
  • Data Storytelling
  • Coding & Automation
  • Business & Strategy
  • Marketing & Branding
  • Stakeholder Management
  • Another capability adapted to your needs
  • Work on your project(s)
  • Receive feedback
  • Iterate

Week 4 - Data Analytics

What we’ll be doing

  • Discover the fundamentals of evidence from data
  • How: by executing basic prescriptive analysis using python
  • Build basic data visualizations to explain results from analysis
  • Match the right chart to a specific data type and insights

Tools we’ll be using

  • Google Colab
  • Power BI
  • Tableau
  • Matplotlib 
  • seaborn
  • plotly

Week 5 - Project & T-shaping

Focus on key capabilities to strengthen your T-shape Depending on your skills assessment these could be:

  • Data Analytics
  • Data Wrangling
  • Machine Learning
  • Data Storytelling
  • Coding & Automation
  • Business & Strategy
  • Marketing & Branding
  • Stakeholder Management
  • Another capability adapted to your needs
  • Work on your project(s)
  • Receive feedback
  • Iterate

Week 6 - Machine Learning

What we’ll be doing

  • Discover the fundamentals of predictive models
  • How: by executing the basic steps of classification models. Using: python and low code tools
  • Understand the basics of the process of training, testing and deploying predictive models
  • Evaluate the performance and interpretability of different classification models, such as neural networks, random forest and logistic regression

Tools we’ll be using

  • Dataiku
  • Google Colab
  • scikitlearn
  • keras

Week 7 - Self Study: Machine Learning

What we’ll be doing

  • Discover the main hyperparameters of supervised learning
  • How: by executing the basic steps of continuous values predictions. Using python and low code tools
  • Understanding the basic methods used to build robust predictions, such as regularization, cross-validation
  • Understand the performance metrics used to evaluate continuous values predictions
  • Build models based on these understandings

 

Tools we’ll be using

  • Dataiku
  • Google Colab
  • scikitlearn
  • statsmodels
  • keras

Week 8 - Machine Learning

What we’ll be doing

  • Discover the fundamentals of unsupervised learning
  • How: by executing the basic steps of clustering models. Using: python and low code tools
  • Understand the applications of k-means and hierarchical clustering in customer segmentation
  • Discover the applications of unsupervised learning in customization and persona building
  • Evaluate the performance of algorithms according to a proper business metric, e.g precision, recall, silhouette, mean squared error

 

Tools we’ll be using

  • Dataiku
  • Google Colab
  • scikitlearn
  • keras

Week 9 - Project & T-shaping

Focus on key capabilities to strengthen your T-shape Depending on your skills assessment these could be:

  • Data Analytics
  • Data Wrangling
  • Machine Learning
  • Data Storytelling
  • Coding & Automation
  • Business & Strategy
  • Marketing & Branding
  • Stakeholder Management
  • Another capability adapted to your needs
  • Work on your project(s)
  • Receive feedback
  • Iterate

Week 10 - Self Study: Storytelling with Data

What we’ll be doing

  • Build upon the fundamentals of effective visualization of exploratory and explanatory data analysis
  • How to select the right visuals. Data Visualization checklist. Why you should choose some visuals over others and how to communicate your decision
  • Understand the data visualization best practices and how to execute a quality check
  • Discover the main tools and packages used currently for data visualization.
  • Exploratory vs. explanatory analysis
  • Creating visuals that deepen your knowledge and visuals that support your story
  • Simplifying and avoiding clutter. Communicating clear and memorable messages

 

Tools we’ll be using

  • Google Colab
  • Power BI
  • Tableau
  • matplotlib
  • seaborn
  • plotly

Week 11 - Project & T-shaping

Focus on key capabilities to strengthen your T-shape Depending on your skills assessment these could be:

  • Data Analytics
  • Data Wrangling
  • Machine Learning
  • Data Storytelling
  • Coding & Automation
  • Business & Strategy
  • Marketing & Branding
  • Stakeholder Management
  • Another capability adapted to your needs
  • Work on your project(s)
  • Receive feedback
  • Iterate

Week 12 - Storytelling with Data

What we’ll be doing

  • Build upon the fundamentals of effective presentation of results from data analysis
  • Evaluate the components of an effective communication of results:  analysis, narrative and visuals.
  • Execute a presentation of basic results in a way that people can understand and remember it
  • Story structure. Telling a story with a clear beginning, middle and end. Highlighting conclusions and takeaways. Selecting the right level of detail, from helicopter view to deep dive
  • Use of character. Finding relatable elements. Bringing data to life
  • Use of analogies. Removing jargon and explaining models in simple language
  • Slide design. Conveying concise messages without distracting your audience from your speech
  • Presentation tips. Mastering the connection with the audience to take them on a data journey

 

Tools we’ll be using

  • Google Colab
  • Power BI
  • Tableau
  • matplotlib
  • seaborn
  • plotly

Then in 12 weeks.. You become a 'T-Shaped' UX designer

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The T-shaped UXer is a cross-functional asset. They possess a broad width of knowledge complemented by a deep understanding of user experience design. They earn more and are more adaptable.

Some Of The Companies Our Alumni Work At

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ing logo
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IBM Logo
spotify logo
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Pricing & Payment Options

€2997 (incl. VAT)

Option: Payable in 4 payments of €749

Dates

Pick a date to start the learning!

Online Live

June 4th – August 20th

GT-2DCC

Every Thursday, 6:30 pm - 9:30 pm, CEST

Online Live

August 19th – November 4th 

GT-2DCC

Every Thursday, 9:30am - 12:30 pm, CEST

Online Live

August 27th – November 12th 

GT-2DCC

Every Thursday, 6:30pm - 9:30 pm, CEST

Gain access to our exclusive alumni community

As a Growth Tribe alumni, you will join a community of over 15,000 professionals and gain exclusive access to:

  • Events, roundtables & workshops
  • Online Slack & Facebook groups
  • Online Content
  • New Courses
  • Networking opportunities

And much more…

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Business Solutions

Part of a company? Looking to learn as a team? We do that too...

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