January 27, 2020 0

By Akinsande Lekan

Natural Language Processing (NLP) is at the core of research in data science these days and one of the most common applications of NLP is sentiment analysis. Also known as “Opinion Mining” or “Emotion AI” Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.

From opinion polls to creating marketing and public policy strategies, sentiment analysis has completely reshaped the way businesses and governance work, which is why it is an area everyone(both techies and non-techies) must be familiar with.

In this article, we will learn how to carry out Sentiment Analysis on twitter data by using Orange3 Text Mining, Vader and Microsoft PowerBi. Orange3 will be used to stream tweets from Twitter, Vader will be used for the sentiment Analysis and PowerBi will be used to create a sentiment analysis dashboard. Beyond twitter data, the knowledge gained from this tutorial can be used for sentiment analysis on any text data(surveys, polls,etc.)

There can be two approaches to sentiment analysis.

1. Lexicon-based methods

2. Machine Learning-based methods.

We will be using VADER (Valence Aware Dictionary and sEntiment Reasoner) a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media.

Let’s build the solution now!

Step 1: Getting the Twitter API Credential

To access the developer account, you need to have a twitter account. In order to access the Twitter API, you need to register an application at http://apps.twitter.com. On the top-right corner, click on the Apps button, Create an App, Apply and then Continue. Next, we will choose the “I am requesting access for my own personal use” option:

On the same web page, scroll down a bit and input your Account name and Country of operation then click Continue, and you will be redirected to the next web page. Here, you can choose any Use Cases you’re interested in. For our case, I chose the following:

After you make your choice, scroll down and fill out the use case interest paragraph required. This tutorial is for learning, so make sure you emphasize on the application being a self-learning/academic-related project. Choose “No” for the government involvement question, and press “Continue”. On the next web page, read the Terms and Conditions list, agree to them then Submit Application. Now, you have to wait for Twitter to verify your developer account.

When you get the approval email, click on the login link it contains. You will be redirected to the following web page, where you should choose “Create an app”.

On the next web page, click “Create an app” from the top-right corner. After you are redirected, fill out the required app details, including — if you’d like — that it is for self-learning purposes. Click “Create”.

The next web page will include the app details that you just input, access tokens and permissions. Proceed to the “Keys and tokens” tab. Copy the API key as well as the API secret key into a safe place (a text file, if you’d like), as we will be using them in a bit. We’re done with the credential acquisition part!

Step 2: Download and Install Orange3 Text Mining

If you already have Anaconda installed on your computer, you can install orange3 from the Anaconda Navigator.

On the other hand, Orange3 can be downloaded from here: https://orange.biolab.si/download/#windows for windows users; https://orange.biolab.si/download/#macos for mac users; https://orange.biolab.si/download/#linux for Linux

Now that you have Orange3 downloaded, go ahead and install it.

Step 3: Orange3 + Vader for Twitter Streaming and Sentiment Analysis

Now that you have installed Orange3, open the application:

This is the welcome page for Orange3

Click “New” to launch a blank canvas. Orange3 offers a lot of analytics capabilities for data preprocessing, visualization, statistical modelling, and machine learning. You can watch more tutorial videos on their YouTube channel via the link: https://www.youtube.com/channel/UClKKWBe2SCAEyv7ZNGhIe4g/videos

Text Analysis doesn’t come with Orange3 by default, so we need to install the Orange-Text addon. To install, click “Options” on the home ribbon and select “Add-ons…”. Check the Orange3-Text and click okay; wait for the add-on to install.

Orange3 Add-ons window

Now that you have the Text add-on installed, let’s build the flow!

This is the flow that we will build

Follow these steps to build the Orange3 sentiment analysis flow:

  1. The Twitter Widget: Expand the Text Mining drop down on the left panel; drag and drop the ‘Twitter’ widget to the canvas.
  2. The Data Table: Expand the Data drop-down on the left panel; drag and drop the ‘Data Table’ widget to the canvas. Connect the ‘Twitter’ widget to the ‘Data Table’ by dragging any part of the dotted arc of the ‘Twitter’ widget to the ‘Data Table’ widget. NB: This is how you create connections between widgets.
  3. The Save Data: Expand the Data drop-down on the left panel; drag and drop the ‘Save Data’ widget to the canvas. Connect the ‘Data Table’ widget to the ‘Save Data’.
  4. The Preprocess Text: Expand the Text Mining drop down on the left panel; drag and drop the ‘Preprocess Text’ widget to the canvas. Connect the ‘Twitter’ widget to it.
  5. The Word Cloud: Expand the Text Mining drop down on the left panel; drag and drop the ‘Word Cloud’ widget to the canvas. Connect the ‘Preprocess Text’ widget to it.
  6. The Sentiment Analysis: Expand the Text Mining drop down on the left panel; drag and drop the ‘Sentiment Analysis’ widget to the canvas. Connect the ‘Preprocess Text’ widget to it.

Now that you have successfully set up your workflow, let’s discuss how we would work with each of these widgets to create our sentiment analyzer.

The Twitter Widget

Double click the ‘Twitter’ widget and the configuration window opens up:

Configuring the Twitter Widget

Click the ‘Twitter API Key’ button and input you ‘Consumer API Key’ and ‘Secret Key’ that was generated in Step 1

For this tutorial, we will stream 1000 tweets where the word mbuhari(the official twitter handle of the Nigerian President, President Muhammadu Buhari GCFR) was mentioned. So, if you would like to follow this article religiously, input ‘mbuhari’ in the query word list box and set the max tweets to 1000. Click ‘Start’ to start streaming data from twitter. (tweets streamed on January 19th, 2020)

The Data Table Widget

In this workflow, we made use of two ‘Data Table’ widgets. This widget allows us to view the data in a table format. The first data table is connected to the ‘Twitter’ widget. We can view this data by double-clicking the ‘Data Table’ widget.

The Save Data Widget

This widget saves data from the data table as .csv. Double click this widget to define the name and path for your file.

Note: ‘Save Data’ will only save the highlighted data on the ‘Data Table’. So, to highlight data on the data table, double click the ‘Data Table’ widget to open the ‘Data Table’ Window. Double click the ‘title’ on the top left corner of the table, the entire data table is highlighted and automatically saved to .csv

Highlighted data table will be saved

The Pre-process Text Widget

This constructs a text pre-processing pipeline. It allows us to transform, tokenize and filter our data. Double click the widget to open the Preprocess window. We want to transform our data by maintaining lower case in all tweets, removing accents, parse HTML and removing URLs; so, please check all the boxes under the Transformation section.

Under Tokenization, we are only interested in splitting by regular expressions and keeping only words. Select Regexp and type \w+ as the pattern.

Under Filtering, we will remove stop words in the English language. So, check ‘Stopwords’ and set language to ‘English’

Preprocess Text window

The Word Cloud

This widget is one of my favorite text analytics visuals. It helps you see the most mentioned words in text data. See what our cloud looks like:

The Sentiment Analysis

Double click this widget and select Vader. VADER uses a combination of a list of lexical features (e.g., words) which are generally labeled according to their semantic orientation as either positive or negative. VADER not only tells about the Positivity and Negativity score but also tells us about how positive or negative a sentiment is.

Next Part

The ‘Data Table’ that connects to the ‘Sentiment Analysis’ widget contains the tweets and the sentiment score. This is the data that we are interested in; it will serve as a database for our interactive dashboard. In the next part of this tutorial, we will explore how to create a fully functional sentiment analysis dashboard with PowerBi.

See you then!

I hope you found this tutorial interesting. Please share and remember to clap.


You can follow me on Twitter @akinsande1

Read Part 2 here: datasciencenigeri.org/SimpleSentiment2


December 30, 2019 0

JanuaryJanuary 6Full resumption at the AI Hub Yaba office
January 11 – February 29Saturday Professional Business Analytics Training new cohort classes
January 12Kick off of NLP, Geospatial and Health Data workstream at AI Hub
January 17Train-the-Teachers Artificial Intelligence Masterclass and book distribution in Owerri, Imo State.
January 20Kick-off of AI+ Clubs in secondary schools as an after-school club in Lagos secondary schools
January 25The SeqHub/Maxng/DSN Ideathon – AI Hub
FebruaryFebruary 5 - March 11Beginners AI Wednesdays 6-week intensive introduction to Python and Machine Learning
February 6 - March 12Pre-University Training in 5 states on Introduction to Python and Machine Learning
February 10Association for the Advancement of Artificial Intelligence Conference - AI for Social Impact
February 15 - April 30Kaggle competition
TBDRetina-AI AI DevOps Hackathon
February 27Train-the-Teachers Artificial Intelligence Masterclass and book distribution
February 261-day Masterclass in R programming
MarchTBDAI Invasion in 50 cities (1-week intensive introduction to Python/Machine Learning in 50 cities in Nigeria)
March 21 – Jun 13Weekend Certification classes in BigML, Columbia/Edx and Microsoft Azure
TBDData Science for Marketing: 3-day intensive corporate training
TBDTrain-the-Teachers Artificial Intelligence Masterclass and book distribution
March 28AI+ Dial-in Masterclass: Reinforcement Learning
AprilApril 3AI for Financial Inclusion workshop
TBDReadiness Kaggle/Zindi Mini-competition - Best participants win books and tickets to tech events
April 241-day Masterclass in Natural Language Processing
April 29-30AI Researchers Conference – International conference hosted in Lagos
April 29-30Participation at ICLR Ethiopia [Virtual Conference]
MayMay 4-8AI for Good Global Summit 2020, Geneva, Switzerland : Attendance and showcase
May 151-day Masterclass in Data Engineering
May 16Data Visualization with Microsoft PowerBI Masterclass : 5 Saturdays intensive corporate training
TBDBeginners AI Wednesdays 6-week intensive introduction to Python and Machine Learning
TBDPre-University Training 6-week class on Introduction to Python and Machine Learning
TBDData Science for Human Resources/People Analytics : 3-day intensive corporate training
May 21-22PhD Research Paper writing workshop with Dr Elaine Nsoesie [Virtual Training]
May 28Fall in Love with AI – Women meet up on AI Career development
JuneJune 12Machine Learning Masterclass in collaboration with Google
June 13AI+ City and Campus Ambassadors Conference in Lagos
June 25 – August 24Pre-Bootcamp 60 days of Machine Learning and Deep Learning
June 30Release of whitepaper on AI-powered Citizen Science on Digital Marketing/Social Media
TBD1-day Masterclass in Microsoft Azure DevOps
TBDDeep Learning Masterclass : Intensive virtual corporate training
JulyTBDAI+ for Professionals Meet-up
TBDData Science for Banking/Fintech/Insurance : 3-day intensive corporate training
TBDRobotic Process Automation Masterclass: 2 Saturdays intensive corporate training
TBDData Science for Technical professionals: 3-day intensive corporate training
AugustTBDBusiness/Data Analytics for Professionals: 2 Saturdays intensive corporate training
TBDMasterclass on AI for Project Monitoring and Evaluation for non-profit
TBDData Engineering: 2 Saturdays intensive corporate training
TBDAI Summer School for Grades 5-9
TBDArtificial Intelligence and Financial Inclusion Research meet-up
TBDLadies in AI Meet-up
TBDDeep Learning Indaba Tunisia – participation and poster showcase
SeptemberTBDAI Bootcamp 2020 Selection Kaggle/Zindi Competition
TBDData Analytics with Microsoft Azure and BigML : 2 Saturdays intensive corporate training
September 25
September 26AI Bootcamp 2020: Call for posters
TBDGame theory and Mechanism design Masterclass : 2 Saturdays intensive corporate training
OctoberOctober 1Release of our AI Blueprint for Nation Building – 60 Imperatives for AINaija as part of Nigeria’s 60 th Independence anniversary
October 20AI Summit 2020: AI for 21 st century Governance and Business Success
October 22AI Masterclass for Executives and Business Leaders
October 20 - 25AI Bootcamp – 4 streams sessions (Beginners, Intermediate, Advanced Researchers and Professional streams) – an intensive fully residential and all-expense paid for best 250 best students, researchers and young professionals.
NovemberNovember 2Release of DSN whitepaper on AI-powered Citizen Science on Natural Language Processing and Health using Twitter Data
TBDBeginners AI Wednesdays 6-week intensive introduction to Python and Machine Learning
TBDPre-University Training 6-week class on Introduction to Python and Machine Learning
TBDDeep Learning Masterclass - CNN
TBDDeep Learning Masterclass - RNN
DecemberDecember 2 - 8 (TBD)NeurIPS 2020 Vancouver, Canada - attendance and poster showcase
December 7 - 8Local NeurIPS meet-up at AI Hub, Yaba
December 18 - 20Data Science Nigeria team annual strategy retreat/team building
December 23AI Hub Team End-of-year party/Business closes for the year


December 27, 2019 0

2019 Milestones at Data Science Nigeria

We have had a very awesome 2019. We have activated our vision to raise one million Artificial Intelligent talents in 10 years. We have scaled up sustainability and built unique platforms to support our operation and expansion.

We are indeed very grateful to our inspiring staff, awesome sponsors, amazing advisory board members, supportive partners, and the ever-energetic community members.

Of a truth, we are well-positioned to achieve our mission to build a world-class Artificial Intelligence (AI) knowledge, research and innovation ecosystem that delivers high-impact transformational research, business use applications, AI-first start-ups, support employability, and social good use cases in Nigeria and beyond.

Read some of our major milestones in 2019













































December 11, 2019 0

Lagos NeurIPs Meetup Programme Schedule
Venue: AI Hub, 174b Murtala Muhammed Way, Yaba
(4th floor Sunu Assurance Building)

Friday 13th of December, 2019
4:00 – 4:15: Welcome & Data Science Nigeria Introduction
4:15 – 4:30: NeurIPS introduction
4:30 – 5:00: Living is an Agricultural Act: AI for Global Food Security by Sarah Menker
5:00 – 5:30: Discussion on Data Science Nigeria AI class monitor
5:30 – 6:25: Veridical Data Science by Bin Yu
6:25 – 7:15: Social Intelligence by Blaise Aguera y Arcas
7:15 – 7:30: Book Winning Time
7:30 Menu: Finger food and drink

Saturday 14th of December 2019
10:00 – 10:15: Welcome
10:15 – 10:50: Machine Learning Meets Single-Cell Biology: Insights and Challenges by Dana Pe’er
10:50 – 11:40: How to Know by Celeste Kidd
11:40 – 12:10: Discussion on Data Science Nigeria AI class monitor
12:10 – 12:50: From System 1 Deep Learning to System 2 Deep Learning by Yoshua Bengio
12:50 – 1:30: Women in Machine Learning (WiML) Affinity Workshop 2
1:30 – 1:45: Book Winning Time
1:45 Menu : Finger food and drink

To register, click Here


December 9, 2019 0

As a part of Data Science Nigeria’s transition from an Artificial Intelligence learning community into a research and consulting non-profit, the business is expanding its dedicated workforce with the recruitment of three new data scientists. The new, young and energetic data scientists will be working on a special project at the interception of advanced analytics, statistical model development, data visualization and platform development for real-time analytics.

Join us to welcome 3 awesome ladies into our Data Science core team.

Meet the new team members
Sarah Opeyemi Adekunle, Data Scientist:
A Masters’s graduate of Systems Engineering. She is a product of the Microsoft4afrika where she groomed her skills in Data Science and Business Intelligence. She has built industry-level experience in Data Analysis, and Machine Learning use cases. She was the second-best female participant (4th position) at the 2017 Data Science Nigeria Artificial Intelligence Bootcamp.

Chimaoge Esotu, Data Scientist:
A passionate data scientist with a passion for trends mining. She has built competencies in skilled statistical analysis, machine learning and various types of database management. She has had industry level experience as a data analyst and business performance reporting expert. Chimaoge has hands-on experience in many visualizations, analytical and mathematical programming tools.

Haleemah Oladosu, Data Scientist:
A multi-skilled professional who combines her machine learning skills with software engineering and IT support Administration. An ex-Andela software engineer and a Kaggle participant per excellence with 9 competitions in her kitty. She was in the Top 2% in the Women in Data Science (WiDS) Datathon 2019. She had a Master’s degree in Artificial Intelligence/Data Mining.


December 4, 2019 0

In its quest to raise 1 million Artificial Intelligence (AI) talents in 10 years and position Nigeria as a leading AI Hub, Data Science Nigeria (DSN) has expanded its learning community model to include a data science consulting and AI solutions delivery. In the last few months, the organisation has delivered solution-oriented machine learning projects, corporate trainings and bespoke consulting to local and international organisations with outstanding commendation of quality.

In order to strengthen its team, the organisation has expanded its consulting and operations workforce with experienced business and growth hacker, technical consulting lead, statisticians/data scientist, software engineers and grant/finance management expert from leading local and global organisations. The new model will also afford DSN a platform to scale up, ensure sustainability through self-funding, validate the Nigeria AI ecosystem, accelerate business use cases and provide hands-on learning opportunities for many DSN members (students, young professionals and beginners) across the country through paid internship and project participation.

Meet the new talents in the team

Michael NwosehStrategic Growth Lead: An experienced business manager, stakeholder and project management expert with 10 years commendable career in the Telecom and Banking industry. He has broad expertise in implementing strategic plans, conducting market research and driving execution excellence. He is also an expert in youth market engagement and strategy development, which is critical in driving our vision to raise 1million AI talents in 10 years.

Olalekan AkinsandeTechnical Delivery Lead: An experienced Data Scientist, Robotics Process Automation(RPA) Developer and Project Manager who previously worked with KPMG Data & Analytics team. Olalekan is proficient in building, deployment and management of end-to-end Data Analytics and Process Automation solution. He has broad experience in leading Data Analytics and Process Automation projects for Clients in the Financial Services, Oil & Gas, Telecoms, Manufacturing, FMCG, Transport and Utility industry.

Olusola Oseni– Software Engineer: An ex-Andela software engineer who will be driving how we find operational fusion of AI and software engineering in solving social and business problems. With PhD grade in his Petroleum Geology postgraduate studies, he has found a new passion in building solutions. He worked for 18 months as a freelance Software Developer before moving to Andela where he was a resident Software Developer and Technical Coordinator for 19 months. One of his works is a data collection app for a leading multinational tracking sale from the field.

Ezekiel OgundepoData Scientist: A first-class Statistics graduate with Master degree from African Institute for Mathematical Sciences (AIMS), Rwanda. He is an expert in Advanced Statistical modelling with professional experience at the Rwanda Revenue Authority (RRA) where he worked to build dynamic taxpayers data portal and automated key statistical reports required by internal and external users. He is an R programming guru with a passion for geospatial analytics, advanced data analytics, visualisation and business application for impact. Ezekiel has used the set skills in data cleaning, analysis, machine learning, and analytical storytelling to provide statistical consultancy for clients in 15 countries as a freelancer.

Ebenezer Don-UgwuSoftware Engineer: A vibrant and young full-stack software engineer, an ex- Andela staff member with a passion for building meaningful products that ease the life of users. He has worked with distributed teams and has a strong passion with regard to AI driven software engineering. He is a versatile professional who is keen on finding solutions through cross-bundled experimentation.

Anaeze Nsoffor Software Engineer: He is a full stack Javascript/Python developer who is an advocate of super-efficient programming. He previously worked at Andela and has rich experience in Node.js, C#, Jquery, Reactjs. He will aid in accelerating our solution creation and find beneficial intersections between software engineering and Machine learning solution delivery.

Tunmise Johnson – Grant/Finance Manager: A Chartered Accountant and expert with solid experience in financial/grant management in both private and public development organisations. He previously worked with a Health Strategy and Delivery Foundation where he managed many international grants. His functional experience spans across Financial Management, Grant management, Process Management, Audit and Financial Modelling.

Join us as we welcome these awesome talents.

You can download the Data Science Nigeria corporate consulting and training brochure here


November 6, 2019 0

In 2020, DSN will be expanding to run 24 city-based AI+ learning meet-ups as part of our scale-up strategy to achieve our 1 million AI talents in 10 years. This will be executed via a structured learning platform for secondary school students, pre-university students, university/polytechnics students and professionals, similar to the AIEveryDay model currently being running at the AI Hub in Lagos.
These AI+ meet-ups will be fully funded by Data Science Nigeria and managed professionally with strong focus on curriculum, quality assurance and opportunity creation for all the community members. It will be managed by a dedicated DSN resource, Program Manager in charge of AI Community, Content and Collaboration. He/She will drive learning engagement, partnership development, support, curriculum/content support etc.

What makes our AI+ City Meet-Up different?
• It will encompass all learning segments. For example, we will use our new book on AI for Primary and secondary schools to train Primary/JSS students during holidays/midterm breaks
• All the tutors and city leads are verified and validated instructors who will also be attending regular DSN classes and workshops on regular basis for quality assurance
• Students who are part of these learning communities will have access to DSN internship, virtual work opportunities and job recommendations – especially with our growing project consulting portfolio for local and international clients.
• Each will be fully funded by Data Science Nigeria and operate in partnership with a local facility provider (Hubs/ Campuses etc.)
• The City Lead will also be responsible for our high-impact strategy to get AI into all primary and secondary schools in Nigeria via a Train-the-trainer programme to equip primary and secondary school teachers across Nigeria with the right basic skills to use our new book on AI/Python programming as part of the curriculum

Benefits for the City Leads
• Access to all DSN mentoring, travel grants and support platforms.
• Participation in DSN projects as a way to earn extra income, particularly through our DataCrowd product.
• Access internship at DSN office in Lagos and DSN partner companies
• Recommendation for DSN third party job placements and scholarship opportunities
• Selected candidates will receive special slot to attend the 2019 AI Bootcamp as part of their capacity building and briefing programme (if they are not currently on the list).

(1) Selected candidates with good experience that can be validated via Kaggle/GitHub/Zindi
(2) Excellent community building and relationship skills that can be proven
(3) The AI City Lead must be available in the city for the next 6-12 months

Cities of Interest:

  • Abuja
  • Sokoto
  • Kano
  • Zaira
  • Jos
  • Bauchi
  • Gombe
  • Yola
  • Ilorin
  • Ibadan
  • Kaduna
  • Lokoja
  • Abeokuta
  • Ijebu-Ode
  • Osogbo
  • Akure
  • Ado-Ekiti
  • Benin City
  • Owerri
  • Enugu
  • Calabar
  • Uyo
  • Port Harcourt
  • Asaba

To Apply: Click Here


October 21, 2019 0

In our drive to be a world-class centre of academic research, AI social good solution development, consulting, capacity building and talent pipeline development; we have openings for extremely motivated, brilliant and passionate talents who share in our vision to raise 1million AI talents in 10 years

We cherish our values as a fun-filled, family-oriented, responsible, innovative and knowledge-driven non-profit that is scaling up very fast with global credibility and increasing local endorsement.

We have openings in these areas for some awesome projects we are working on and so many others on the queue:

Find the detailed description for each role attached below

Application Developer for AI solutions

Solution Development Lead

Product Growth and Research Lead

Vacancy Programme Director DSN

Data Architect

Data Scientists Analytics and Visualization

Geospatial Data Interns and Analysts


October 16, 2019 0

We are excited to welcome Wuraola Oyewusi, a pharmacist and data scienstist who joins Data Science Nigeria as the Lead for Research and Innovation. She is a passionate professional committed to advancing Artificial Intelligence practice. She previously worked with eHealth Africa (eHA), a US firm with the largest data-driven health delivery system in Africa.

She is well recognized in the AI community for her work on Scispacy.Click Here to view it

She has also been in the forefront of the unstructured data application and open source access, especially in the area of health. She developed #NLP Datasets related to health, which she made open to global acknowledgement. Dr Stephen Odaibo of RetinaAI USA (one of our Advisory Board members) actually did a tweet on this Click Here to see attached. The open source dataset is useful for Topic Modelling, Sentiment Analysis, Text Pre-Processing and even more.

She is a Pythonista whose contribution to Pandas was recognized by Marc Garcia. The post on her Pull Request being merged on pandas was a celebration for the Nigerian AI community.Check Here

She was also part of the NLP project led by Dr Wale Akinfaderin (Duke Energy USA) which recently won a grant from the Canadian/Swedish government backed AI4Development on the use of NLP for parliamentary document analysis

Wura has grown to be an end-to-end machine learning and deep learning user with documented proof of study/applications in topics like Sequence Models, Deep Learning, End to end ML with Tensorflow, Time series, Recommendation systems and lately Google IT support Check Here

You can check many of her works via Github repo: Here
At Data Science Nigeria, Wura will be driving our research works, publications/contribution to knowledge, supporting the Knowledge leadership that DSN is known for, application of theory into solution development, leading DSN proprietary in-house bespoke AI suites, consulting support for clients and partners, mentoring of in-house researchers, teaching, project management related to our core solutions and support for ongoing solution development (AI Class Monitor, NaLie, DataCrowd etc.)
Please join us to welcome her with your usual support and camaraderie. She is accessible via email at wuraola@datasciencenigeria.ai


June 27, 2018 1

Dr. Moustapha Cisse1 was recently appointed as the Lead of the Google Artificial Intelligence (AI) Research Lab in Accra, Ghana, the first Google lab in Africa. It might interest you to know that Moustapha’s journey in AI began when he started designing an algorithm for a strategic game while studying for a Math and Physics degree at a Senegal university. He then went on to study Machine Learning with a Masters and a PhD degree in Paris, France. After spending some time working at Facebook AI Research, he has moved to lead Google’s AI expansion strategy in Africa. Moustapha is an AI technical researcher, hands-on expert and proactive knowledge champion with an inspiring vision for AI in Africa. Below we list ten facts about Moustapha Cisse.

  1. An Axiological AI Expert

Moustapha is a strong believer in AI for social good. He believes that the most fundamental role of Artificial Intelligence is to enrich and enhance the quality of living while also enabling the core values of a society.  Speaking at the ITU’s AI for Good Global Summit2, 3 last June in Geneva, he stressed that developments in AI should aim at making our societies better. He believes that AI should have a direct positive impact on peoples’ lives, in particular, education and healthcare. AI research and applications should be aligned with societies’ values and needs.  It must be anchored on the essence of a society as an enabler of common good.

  1. Advocate for AI as a Solution to Local Problems

Using AI to solve specific local community problems has been another career drive for Moustapha. For example, with regard to malnutrition in Africa, he proposes building AI systems and datasets to predict nutrition crises and also to provide insight for proactive actions4. Moustapha argues that joint partnerships should be established between policy makers and the AI community to build intelligent solutions to local nutrition challenges5. He was very passionate about these issues at the African Green Revolution Forum (AGRF), which took place in Abidjan, Côte d’Ivoire in 2017.

  1. Concerned with the Limitations in Datasets

“You are what you eat, and right now we feed our models junk food”6. Moustapha emphasizes the need to focus on making our models less biased by relying on high quality and less noisy datasets. He believes that in order to remove bias and inequality, data trust mechanisms should be used to evaluate the input data that AI products and platforms currently rely on.

  1. Believes that AI Bias is more fundamental

Moustapha believes that the AI bias problem is fundamental and can be eliminated only by trustworthy and quality datasets. He advocates a non-discriminatory definition of AI problems seeking to tackle global issues, not just white-centric ones2. Moustapha argues that the AI community should explore many important problems to be solved in developing world, and not only the stereotypical white or male only issues.

  1. Active Participant in African Talent Development

Moustapha is committed to supporting AI development and growth in Africa. His vision for AI in Africa and his technical contribution to the field makes him an inspirational role model for young talented Africans to follow. Moustapha is an influential participant in many African AI talent development and capacity building events. He was a speaker at the Data Science Africa 2016/2017 Summer School, in Uganda/Tanzania respectively7. During that event Moustapha had an active role in the Data Science in Africa Workshop, aiming to develop an engagement framework for young African talent to get more involved in using big data and real time data analytics to solve community problems. Moustapha will be participating in the Deep Learning Indaba8 in September 2018, to be held in South Africa. In collaboration with other prominent AI participants from the continent, Mustapha is genuinely committed to enhancing African involvement in the advancement of AI.

  1. Open Access Advocate

Collaborative, open and free access to knowledge has been central to Moustapha’s personal development. Therefore, he is a strong advocate of open access as a driving force for innovation. Recently, he signed an agreement to boycott the Nature’s Machine Intelligence Journal due to its lack of open access9.

  1. Co-Founder of Black in AI Group

Dr. Moustapha Cisse is a co-founder of a number of AI and machine learning African groups including the BlackinAI10 group, which aims at enhancing black people involvement in AI via sharing ideas, collaborations and initiatives.  He was one of the organisers of the 1st ever Black in AI event, which took place at Neural Information Processing Systems (NIPS)  2017 in California, USA, with a clear goal to increase the presence of Black people in the field of artificial intelligence, for both diversity and data bias prevention purposes. He co-founded BlackinAI with Timnit Gebru (Microsoft Research, NYC), Rediet Abebe (Cornell PhD), Sarah M. Brown (University of California, Berkeley), Sanmi Koyejo (University of Illinois) and Lyne P. Tchapmi (Stanford University). BlackinAI  is driving capacity building through conferences and mentorship, while also driving better representation of the black community in the emerging global AI community. It has over 600 members from Africa, Latin America, Asia, Europe, and North America. With over 200 women members.

  1. Extensive AI Researcher

As an active AI researcher, Moustapha’s has many publications in respected international journals and conferences11. His research interests the issue of trust in AI, tackling issues of safety, security, fairness and bias12. Recently, he has been working on understanding and generating adversarial models to evaluate the robustness of AI systems. Such models can benefit speech recognition and semantic segmentation in applications such as personal assistants and self-driving cars. Moustapha has also been working on creating defences for adversarial models. Biases in datasets has been another research issue considered by Moustapha. His research findings show that deep learning models based on popular datasets sometimes learn biased decision- making rules. He argues that assuming datasets are balanced is not always right. His work concludes that bias in datasets can be due to various reasons including racial issues.

  1. Self-Learner

Once inspired by an AI project in an undergraduate algorithmic course, Moustapha self-learnt the basics of AI by watching YouTube videos. His interest and belief has made him a top-level expert in the field. He is classicial reference of “YOU CAN”, whose path has dramatized the fact that it does not matter where you start from, every child in Africa can go and become the best in their chosen career.

  1. A True African

Being an African has not always been an advantage in Moustapha’s AI research career. In a recent interview12, Moustapha talked about the lack of diversity he and other non-western AI researchers have been facing in the AI community. He emphasized that major AI events are usually organized in Western countries. Moustapha talked about his personal discrimination experiences, such as being denied a visa to visit Australia. Dr. Cisse explained that this prevented him from attending the major ICML 201713 AI conference to present two papers accepted by the ICML. Having said that, Moustapha has always been a proud African who loves his continent. He always encourages others to visit his country, Senegal, and learn more about the African culture. On the AI front, Moustapha Cisse has a vision for Africa to be actively involved in state of the art AI advancements that will solve the continent’s problems in agriculture, health and education. His vision and AI technical capabilities will sustain his great contribution to the AI movement in Africa.

Data Science Nigeria is very excited to have Dr. Moustapha Cisse lead this project in the sub-region. We consider ourselves privileged to be a ready pipeline that can leverage the Google Lab platform for truly transformational AI innovations tailor-made to address millennium development goals in the continent.

Written by: Bayo Adekanmbi, Convener Data Science Nigeria & Chief Transformation Officer, MTN Nigeria.



[1] http://moustaphacisse.com/

[2] https://www.youtube.com/watch?v=seHc3QyDDtc

[3] https://www.itu.int/en/ITU-T/AI/Documents/Report/AI_for_Good_Global_Summit_Report_2017.pdf

[4] https://core.ac.uk/download/pdf/132696902.pdf

[5] https://www.afdb.org/en/news-and-events/experts-call-for-early-warning-systems-against-malnutrition-in-africa-17333/

[6] https://venturebeat.com/2018/05/02/datasheets-could-be-the-solution-to-biased-ai/

[7] https://www.datascienceafrica.org/dsa2016/

[8] http://www.deeplearningindaba.com/speakers2018.html

[9] https://motherboard.vice.com/en_us/article/a3yxwb/ai-researchers-are-boycotting-natures-new-machine-intelligence-journal

[10] https://blackinai.github.io/

[11] https://dblp.uni-trier.de/pers/hd/c/Ciss=eacute=:Moustapha

[12] https://www.youtube.com/watch?v=dRWV_LGFGy4

[13] http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=53557