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About Me

Ivo Mbi is a Cameroonian by birth and currently residing in Belgium with over 5+ years of working experience in data related fields such as database designer, developer and administrator and data analyst, helping companies store, manage, extract and make sense out their data. His successes have been backed by a rich and diverse educational background with degrees in data science, statistics, Health economics and Biochemistry. Not leaving out key certifications such as Microsoft Certified Azure Data Scientist Associate and SAS Certified Specialist in Machine Learning Using SAS Viya 3.4 just to name a few. He is very passionate about helping business make data driven decisions. While looking forward to become a chief data officer in the future, he intends to pick up positions such as Data Engineer, Machine Learning Engineer, Data Scientist, Data Analyst. Lately , reading books and doing writeups excites him and makes him a better person.alt text

Personal Info

Kubam Ivo Mbi
+32489500135
Kerkstraat 30, Tienen Belgium
[email protected] / [email protected]
LinkedIn

Education

Université Libre de Brussels, Belgium
Advance Master: Data Science, Big Data
2020 - 2021

University of Hasselt, Belgium
MSc. Statistics
2018 - 2021

Catholic University Cameroon
MSc. Health Economics Policy and Management
2014 - 2016

University of Buea, Cameroon
BSc. Biochemistry
2007 - 2010

Work Experience

Data Engineer/ Data Scientist Intern
DataMinded, Leuven-Belgium
1/3/2021 – 28/5/2021
ACTIVITIES

  • Project: Automated Anomaly Detection (AOD) tool
  • Train, test and evaluated 4 outlier detection models against 6 datasets
  • Best model (COPOD) was then used to detect outliers on a real weather dataset from Brazil.
  • Recommendations for the AOD tool

Microsoft Student Learn Ambassador
Aug 2020 – present
ACTIVITIES

  • Access to Microsoft AI and Machine learning resources and free Azure credits to experiment new ideas.
  • Collaborating with peers around the world to solve problems, share ideas, learn and get international exposure
  • Organize and host community Events of size 10- 30 attendees such as: Introduction to Git and GitHub (8th October 2020), Azure Machine Learning (31st October 2020)
  • Direct contact with Microsoft employees for guidance and exposure to trending ideas

Founder &CEO, Data Analyst, Database Developer and Administrator
SEED Inc. (Start-up): Data Management and Analytics
January 2016–September 2018
ACTIVITIES

  • Created and implemented the company’s vision and mission
  • Led a team of four to developed the company’s short- and long-term strategies
  • Maintained awareness of the competitive market landscape, negotiated strategic deals to expand company’s opportunities
  • Set up strategic goals and made sure they are measurable and describable

ACTIVITIES AS HEALTH/BUSINESS DATA ANALYST:

  • Designed, developed and maintained customized RDBMS to replaced paper based systems .
  • Trained staff of sizes 4-10 with close follow-up to ensure smooth transition t to the new computerized system.
  • Coordinate project team of 4- 6 consisting of network, IT, database and software developers.
  • Collected data from relational database, Ensure Data validation and preparation for analysis and produced health and business reports for several decision makers.
  • Assemble and maintain relational databases to ensure no down time.
  • Built and analyze live interactive using PowerBi, SSRS and other reporting tools for the different departments.
  • Query the Relational databases using SQL to answer specific business questions

Health Data Analyst (Contract)
Mary Health of Africa, Fontem-Cameroon
Jan 2018 –April 2018

Health Data Analyst (Contract)
Prestige Health Centre, Mbouda-Cameroon
August – October 2018

Health Data Analyst (Volunteer)
St Blaise Clinic, Bamenda-Cameroon
June 2016 – December 2017

Monitoring and Evaluation officer (Internship) Mbingo Baptist Hospital, Cameroon
August 2015

Business Data Analyst (Contract)
St Michael Academy of Science and Arts
September 2014 – June 2018

Science Teacher (Part Time)
St Michael Academy of Science and Arts, Nkwen-Bamenda
Sacred Heart College, Mankon-Bamenda.
St Paul's College, Nkwen-Bamenda.
September 2012 - June2014

Certifications, Training & Awards

Microsoft Certified: Data Analyst Associate
June 2021
Skills Acquired: Prepare the data, Model the data, Visualize the data, Analyze the data, Deploy and maintain deliverables using PowerBi

Microsoft Azure AI Fundamental
April 2021
Skills Acquired: Describe Artificial Intelligence workloads and considerations, fundamental principles of machine learning on Azure, features of computer vision workloads on Azure, features of Natural Language Processing (NLP) workloads on Azure and features of conversational AI workloads on Azure

Linkedin Learning
February, 2021

  • Learning Cloud Computing: Core Concepts
  • Data Science Foundations: Data Engineering

Databricks Academy
December 06, 2020

  • Certificate of Completion of Introduction to Apache Spark’s Architecture
  • Certificate of Completion of Fundamentals of SQL

November 28, 2020

  • Certificate of Completion of Introduction to Big Data
  • Certificate of Completion of Unified Data Analytics

Microsoft Certified: Azure Data Scientist Associate
August 2020
Skills Acquired: Set up an Azure Machine Learning workspace, Run experiments and train models, Optimize and manage models, Deploy and consume models

SAS Certified Specialist: Machine Learning Using SAS Viya 3.4
April 2020
Verification ID: FHLS3SW12N14QCKD
Skills Acquired: Preparing data and feature engineering, Creating supervised machine learning models, Assessing model performance, Deploying models into production

SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling
February 2020
Verification ID: 7YNCPBEKKB1QQWC2
Skills Acquired: Analysis of variance, Linear and logistic regression, Preparing inputs for predictive models, Measuring model performance

SAS Certified Specialist: Base Programming Using SAS 9.4
November 2019
Verification ID: BP368VGK22B1185K
Skills Acquired: Access and Create Data Structures, Manage Data, Error Handling, Generate Reports and Output

Seminars, Events & Hackathons

Event: Project InnerEye
Medical Imaging Deep Learning library to train and deploy models on Azure Machine Learning and Azure Stack
Organizer: Microsoft
Date: 2/11/2021

Event : Introduction to Lakehouse and SQL Analytics Organizer: Databricks 9/2/2021

Event: Project Moab, Project Bonsai
Autonomous Systems from Microsoft
Organizer: Microsoft
Date: 2/3/2021

WHO AFRICA Hackathon
30TH March – 1ST April 2020
ACTIVITIES

  • Brainstorming on the Development of new technological and innovative ideas that could contribute to strengthening the current COVID-19 response in the Africa continent.
    Covid-19 Screening Tool

Hard Skills, Technologies and Personal Projects

Big Data Analytics

Skills: Python, Spark, Data wrangling, Visualization, SQL, Jupyter Notebook, Markdown, spark RDD, pandas, Numpy

Machine Learning

Skills: Machine learning, python, Azure ML, scikit learn, Hyper-parameter tuning, data wrangling, model deployment, Jupyter notebook, pandas, Numpy

Data Visualization

Skills: Vega & Vega-Lite, Altair package, R programming, Latex, Python, ipython Widgets, Matplotlib, seaborn

Time Series Forecast

Skills: Jupyter Widgets, Time series analysis, pmdarima

Software Development

Skills: Hadoop, Apache Spark, MongoDB, Map/Reduce, MySQL, Azure SQL, Git and GitHub, SAS, R, MatLab, Data crunching, NoSQL, BigData, distributed Computing, Azure Cloud Soft Skills:

  • Strong communication and presentation skills
  • Creative, innovative, and strategic thinker
  • Ability to simultaneously coordinate and track multiple deliverables, tasks and dependencies across multiple stakeholders / business areas
  • Leader and team player
  • Proactive attitude, customer oriented and results.

Kubam Ivo Mbi's Projects

azure-machine-learning icon azure-machine-learning

Python has become a dominant language for doing data analysis with machine learning. Learn how to leverage Python and associated libraries in Jupyter Notebooks run on Azure Notebooks to predict patterns and identify trends.

computer-intensive icon computer-intensive

Simulations, Monte Carlo methods, Bootstrap techniques, Randomization methods, Permutation methods.

data-visualisation icon data-visualisation

As data becomes easier and cheaper to generate, we are moving from a hypothesis-driven to data-driven paradigm in scientific research. As a result, we don't only need to find ways to answer any questions we have, but also to identify interesting questions/hypotheses in that data in the first place. In other words: we need to be able to dig through these large and complex datasets in search for unexpected patterns that - once discovered - can be investigated further using regular statistics and machine learning. Interactive data visualization provides a methodology for just that: to allow the user (be they domain expert or lay user) to find those questions, and to give them deep insight in their data. Content Background and context of data visualization and visual data analysis Design as a process: framing the problem, ideation, sketching, design critique, ... Programming visualizations: static and dynamic Project: visualization of expert dataset

generalized-linera-models icon generalized-linera-models

At the end of this course, the student should have a profound knowledge of generalized linear models and basic knowledge of some extensions, including Part I Standard descriptive and inferential methods for multiway contingency t ables (odds ratios, conditional independence, Cochran-Mantel-Haenszel procedures,...) Components of a generalized linear model (GLM) GLM for binary data: logistic regression Building and applying logistic regression models Overdispersion and quasi-likelihood Conditional logistic regression and exact distributions Part II Extensions to multinomial responses (baseline category, cumulative link, partial odds ratio,...) Extensions to clustered binary (GEE, random effects) Extensions to clustered & multinomial data Loglinear models Models for matched pairs The student should be able to apply such models and methods using appropriate software (SAS, R).

house-price-prediction icon house-price-prediction

Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence. With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home.

introduction-to-programming icon introduction-to-programming

A program is an algorithm that can be directly executed by a computer. Learning to program therefore encompasses two complementary skills: (1) constructing algorithms; (2) coding an algorithm as a program. This course focuses on both aspects. We will use the programming language Python. In particular, this course has the following goals: - The student can write simple imperative programs in Python. In particular, he/she can utilize primitive types, strings, lists, iteration, conditions, procedures and functions. - The student understands the importance of precise syntax and semantics. - The student is able to reason about programs and can debug programs. - The student is familiar with the notion of an algorithm, can devise algorithms (for simple problems), and can reason over algorithms. - The student is familiar with the principles of computational thinking and can apply these.

learningsparkv2 icon learningsparkv2

This is the github repo for Learning Spark: Lightning-Fast Data Analytics [2nd Edition]

multivariate-and-hierrarchical-data icon multivariate-and-hierrarchical-data

Contents "Multivariate and Hierarchical Data": - Repeated measures - Clustered data - Multivariate methods. Contents "Discovering Associations": - Sample size calculations - Statistical research for pharmaceutical research and development - Ethical aspects of consulting, reporting - Statistical consulting training & protocol for the design of experiments

ny-taxi icon ny-taxi

Visualisation project for the New York Yellow Taxi

project-learning-from-data icon project-learning-from-data

The aim of this course is to give students the opportunity to collaborate with other students (in a group) and apply, to a real-life dataset, statistical tools and methodology from other courses in the program (Concepts of Probability and Statistics, Linear Models, and Statistical Software and Data Management).

python4beginners icon python4beginners

These threes series on Channel 9 and YouTube are designed to help get you up to speed on Python. If you're a beginning developer looking to add Python to your quiver of languages, or trying to get started on a data science or web project which uses Python, these videos are here to help show you the foundations necessary to walk through a tutorial or other quick start. We do assume you are familiar with another programming language, and some core programming concepts. For example, we highlight the syntax for boolean expressions and creating classes, but we don't dig into what a boolean is or object oriented design. We show you how to perform the tasks you're familiar with in other languages in Python.

us-shootings icon us-shootings

Time Series Analysis of the number of people shoot dead per week by the police in the USA

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