Africa's accountability-driven data science accelerator. Weekly check‑ins, weekly submissions, and a record employers can verify.
At DataraFlow, the work is public, reviewed and visible. By the end, each graduate has projects, articles and a portfolio that can get them hired.
Read the published workOne a week, under your own name.
Real datasets, reviewed by a mentor.
Supervised, then published as a preprint.
Weekly check-ins, all timestamped.
Miss the bar and you leave.
One skill a month, each built on the last.
Setup, programming in Python, and how to do research.
NumPy and Pandas, from first tables to advanced analysis and charts.
Presenting your analysis as a team, then data structures and algorithms.
Collecting data from the web and building first models.
Classification, clustering, and natural language processing.
A preprint of your research, agentic AI, and graduation.
Getting in is competitive and finishing is harder. Every certificate here was earned over a 24-week period of intensive learning and building.
1,580projects gradedand758articles published
2,078applications
275interns on the recordon the programme, finished or graduated
13graduates certified
13 certificates issued. Every one carries a number employers can check.
Verify a certificateEvery week, each intern writes up what they built and publishes it under their own name.
The Challenges Along the WayAbdulazeez Ijaoba
Week 4 & 5: The Weeks I Learned That Research Is Just Structured CuriosityFaustina Ndidiamaka Egbe
Week 6 at DataraFlow: Exploring Data with SQL and PythonOgunseye Oluwaseunfunmi Rofiat
NoneJennifer Udeh
102 BuildingGeorge Nduka
Week 3 : Beyond Basic Scripting: Error Proofing, File Management, and the Jump to Databases.Joshua Onoja
From Folders to a Live Cloud Database: My Week 6 Journey with NumPy, pandas and SQLAbdulwaheed Olasupo
Weeks 4 and 5: Two Rejections, One Verified Topic, and a Proposal I Almost Gave Up OnOluwatimilehin Oluwatuyi
Week 6 at DataraFlow: Making NumPy Stick and Learning Not to Trust Data BlindlyOluwaseyi Olofintila
Working with Python, NumPy, Pandas and SQL: From Data Exploration to InsightsChichi Okafor
From Python Utilities to Practical Problem-Solving: My DataraFlow Week 3 JourneyMohamed Mohamud
From Python Basics to Real-World Problem Solving | DataraFlow Internship — Week 3Taiwo olanrewaju
Week 2 Broke Me: What I Thought I Knew About Python ClassEmmanuel Agbo
Beyond Writing SQL QueriesChristian Oluoma
Bridging the Gap Between SQL Warehouses and Python: My Week 6 Data Science Journey at DataraFlowAustin Ebri
My Week 2 Journey: Learning OOP, Inheritance, Iterators and Polymorphism in PythonZaharaddeen Nura Ibrahim
My Third Week at DataraFlow: Exploring Python Modules and Practical ProgrammingAyooluwa Folorunso
Week 3: The Week Python Started Challenging Me DifferentlyAdedayo Fayoyiwa
From Column Names to Credit Risk: What I Learned in Week 6 of DataraFlowDavid Eyinade
Week 5 at Dataraflow: I Had a Research Topic, But Could I Explain It?Oluwafeyikemi Oladele
Seven Days, Too Many Errors, and a Deadline That Wasn’t Negotiating: My Week 6 Data Science…Balqis Bankole
WEEK 2 AS DATARAFLOW INTERNAmos Akpodoma
I Survived Python, Files, Errors and Somehow Met SQLDennis Otieno
Python ModulesDamilola Oluwole
Week 6: Intermediate SQL, NumPy, Pandas, and a Server That Tested My Sanity…Khadijah Dere
DOCTORS WHO CODE: Week 5 — Can AI Help Us Decide Where Nigeria Needs Robotic Surgery?Irene Udebuana
I Rage-Quit a Video Game Called “SQL Setup” (and Then Beat It)Jennifer Udeh
Python Classes, Methods and Inheritance… DataraFlow Week 2Akinbode Afolabi
Week 3: Beyond Python Basics — Files, Modules, Environments and My First Steps into SQLOlamide Fabunmi
Weeks 4 & 5 of My Data Science Journey: Research, Laptop Wahala, and Learning to Start AgainUncommon Maurice
This Week I Wrestled With Real-World SQL — And Real-World Data WonIfeanyichukwu Aduanya
Week 6 : From NumPy and Pandas to Real-World Weather Data-Cleaning, Joining, and Questioning Data.Abdulkabir Daud
Week 6 learning numpy pandas and sql through practical data workFaith Innocent
Surviving Week 2 of 24: My Python OOP Breakdown (And Why I Almost QuitBolanle M. Adeoye
My Week 3 Journey with DataRaflow: Learning Python Beyond the BasicsKaosarat Ayoade
Data Analysis: Exploring Databases, Working with Data and Driving Insights Using SQL, Numpy and…Marcellus Ifeanyi
What interns and graduates wrote, three months in and after they finished.
Apply to the next cohortThe program has been quite exciting as an opportunity for me, as a young sophomore in college, to break into machine learning and deep learning. I honestly didn't expect it to be this hectic, especially when it comes to balancing it with school. I really wish I could get at least a break or…
The program has been quite exciting as an opportunity for me, as a young sophomore in college, to break into machine learning and deep learning.
I honestly didn't expect it to be this hectic, especially when it comes to balancing it with school. I really wish I could get at least a break or something like that to help me balance things out and stabilize.
That said, the program has been wonderful so far. I'm getting to learn so much, and it's giving me an edge in my career as I learn to break into the space, explore more opportunities, and work on projects.
I really am enjoying it, and I'm grateful for the opportunity.
I am genuinely grateful to still be part of the DataRaflow programme. This journey has tested my resilience, determination, and how far I can push myself despite challenges. Yet, I can see what this experience is preparing me for in the future, and I truly appreciate the opportunity.
I am genuinely grateful to still be part of the DataRaflow programme. This journey has tested my resilience, determination, and how far I can push myself despite challenges. Yet, I can see what this experience is preparing me for in the future, and I truly appreciate the opportunity.
One concern, however, is the intensity of the programme. Although this was mentioned at the beginning, I feel greater emphasis could have been placed on what participants should realistically expect. For future cohorts, providing a clear roadmap of the journey ahead and possibly extending the programme’s duration would help ease the pressure. Personally, I feel the depth of what we are learning could comfortably take about a year to cover, yet we are working to fit it into six months.
Nevertheless, as the saying goes, “What doesn’t kill you makes you stronger.” I believe that by the time I make it through DataRaflow, there will be very few storms in life that I won’t feel equipped to face.
My DataraFlow journey so far has been a mix of learning new concepts, practical assignments, teamwork, and trying to make sense of things that sometimes seem more complicated than they should be😂. From Python fundamentals and OOP to SQL, databases, and data analysis, I have been introduced to…
My DataraFlow journey so far has been a mix of learning new concepts, practical assignments, teamwork, and trying to make sense of things that sometimes seem more complicated than they should be😂. From Python fundamentals and OOP to SQL, databases, and data analysis, I have been introduced to different aspects of data and AI, with each topic bringing its own challenges.
Sometimes, I understand a concept during a lesson but struggle to apply it independently when working on assignments. Writing code, interpreting instructions, and debugging errors have become part of the experience. And SQL? That’s been plenty of “what exactly did I do wrong?” moments🤦
Between revisiting concepts, trying to fix errors, working with my team, and learning through mentorship, It has been challenging but interesting, with moments of frustration and small wins.
I’m learning one step at a time, documenting the process, and growing through the challenges. From Nada to Prada, the journey continues! 💻📊
My experience with DataraFlow has been challenging, when I say challenging I don't mean difficult, i mean it has been challenging me to be better. It's been an amazing journey so far, as someone that was relatively new to tech and data science, the structures put in place, the admins, even those…
My experience with DataraFlow has been challenging, when I say challenging I don't mean difficult, i mean it has been challenging me to be better. It's been an amazing journey so far, as someone that was relatively new to tech and data science, the structures put in place, the admins, even those in the community have been helpful in helping me stay grounded.
I'm really grateful for this program.
I love it here. Interacting with people from a different background. I'm still getting used to hearing the preffix "ma" when addressing someone older. Ii made new friends, and i love the challenge each week brings
My experience with DataraFlow so far has been a journey of learning, growth, and challenging myself to understand new concepts. I particularly love the structure of the DataraFlow app. It is user-friendly, beautifully designed, and makes navigating the learning experience enjoyable.
My experience with DataraFlow so far has been a journey of learning, growth, and challenging myself to understand new concepts. I particularly love the structure of the DataraFlow app. It is user-friendly, beautifully designed, and makes navigating the learning experience enjoyable. I also really appreciate the weekly article concept, which provides an opportunity to engage with topics beyond the practical assignments.
One challenge, however, is that the volume of information to learn and cover within a single week can sometimes feel overwhelming. Having a little more room to digest certain concepts and practise them could make the experience even better. Overall, I'm grateful for the opportunity to learn, build my skills, and keep growing through the programme.
For me, the experience so far has been truly transformational. Looking back at where I started, I can see tremendous progress compared to when I was learning on my own and following random tutorials. I also really appreciate the mentorship structure. My team and I are fortunate to have a mentor…
For me, the experience so far has been truly transformational. Looking back at where I started, I can see tremendous progress compared to when I was learning on my own and following random tutorials.
I also really appreciate the mentorship structure. My team and I are fortunate to have a mentor who genuinely understands what mentorship means and goes beyond simply carrying the title. Honestly, every session, call or conversation with her leaves me with something valuable, and I can already see how much I’m learning and growing.
Above all, I love the drills and the overall structure of the internship. Everything feels intentional, practical, and designed to help us build real skills and grow.
As a Data Science Intern at Dataflow, I gained invaluable practical experience bridging the gap between raw data and real-world decision-making. Working on end-to-end data workflows gave me direct exposure to data cleaning, exploratory analysis, and building machine learning models using Python.
As a Data Science Intern at Dataflow, I gained invaluable practical experience bridging the gap between raw data and real-world decision-making. Working on end-to-end data workflows gave me direct exposure to data cleaning, exploratory analysis, and building machine learning models using Python.
Most importantly, the collaborative environment taught me how to communicate complex technical insights to diverse stakeholders and approach data challenges with a problem-solving mindset. It has been a pivotal step in strengthening my foundation in data science and machine learning.
My experience with DataraFlow has been a valuable learning journey so far. The program is helping me strengthen my Python programming, data science, and machine learning skills through consistent practice and weekly tasks. I am also learning how to approach research, develop a research proposal…
My experience with DataraFlow has been a valuable learning journey so far. The program is helping me strengthen my Python programming, data science, and machine learning skills through consistent practice and weekly tasks. I am also learning how to approach research, develop a research proposal, and stay accountable in my learning. Although some tasks are challenging, they are helping me grow technically and become more confident. I appreciate the structure of the program and look forward to learning more, improving my skills, and completing my research project.
First, I want to thank Dataraflow and the entire team for this rare, no-cost opportunity. I do not take it for granted. I have really enjoyed how structured the internship has been. I have attended paid cohorts before and watched YouTube videos without guidance, but my experience analysing large…
First, I want to thank Dataraflow and the entire team for this rare, no-cost opportunity. I do not take it for granted.
I have really enjoyed how structured the internship has been. I have attended paid cohorts before and watched YouTube videos without guidance, but my experience analysing large datasets was still limited. This internship is helping me put what I have learnt into practice.
I have also noticed an improvement in Python. Before now, I struggled to understand code, but now I can follow it better and debug some errors. For me, this is progress, and it gives me more confidence.
Learning how to communicate my work through publications has also been valuable. I still have a lot to learn, but I can see my progress. Thank you to the team for the guidance and support so far.
My experience at DataraFlow has been very useful, transformative and grounded. Although I was new to some specific part of the work, and many things seemed confusing, the given tasks always pushed me to learn more and move further. The well structured tasks always built me to be more productive…
My experience at DataraFlow has been very useful, transformative and grounded. Although I was new to some specific part of the work, and many things seemed confusing, the given tasks always pushed me to learn more and move further. The well structured tasks always built me to be more productive and be more practical
In particular, my skills in programming languages such as Python have significantly improved. With the help of the obtained experience, I began to understand how to formulate queries correctly and all, I’ve also been applying my knowledge to actual problems.
Apart from the Technical skills, I also gained confidence and competencies that would be helpful to me in future professional challenges and I’ve also been building my online presence Overall, the internship gave me much precious experience that I’ve been putting into practice.
It’s honestly helped me practice data science almost every day. The weekly deadlines can be crazyyy and sometimes the workload gets overwhelming, but I actually think I needed that kind of pressure to stay consistent. I used to procrastinate a lot when learning on my own, so having something I had…
It’s honestly helped me practice data science almost every day. The weekly deadlines can be crazyyy and sometimes the workload gets overwhelming, but I actually think I needed that kind of pressure to stay consistent. I used to procrastinate a lot when learning on my own, so having something I had to show up for every week has definitely helped me get better at staying on track. It’s been stressful at times, but I’ve also learned a lot and gotten more comfortable actually doing the work. So win-win, I guess.
Six months of weekly work, reviewed, and a record you can show anyone.
Apply to the next cohortEvery certificate has a number. Check it, then read the work behind it.
Verify a certificateThe programme is free. Gifts buy laptops and pay school fees, and every gift is listed.
See our impact and donorsInterns submit every week. Mentors grade it and write back.
Apply to be a mentor
