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DISCOVER THE LATEST AND SHARPEN YOUR SKILLS IN AI, DATA SCIENCE, MACHINE LEARNING, AND RELATED TOPICS

Watch our recordings on Data Science, AI, machine learning, data analytics, and more. Also, check out our upcoming webinars.

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Data Science Research Training Program

Join us starting from 7th Febuary 2025 - 26th April 2025

The Data Science Research Training Program is designed to equip enthusiasts in data science, machine learning, and artificial intelligence with the specialized skills and insights needed for a successful academic career. This program emphasizes the unique research methodologies, publishing processes, and scholarship opportunities specific to the tech field, ensuring students are well-prepared to excel in academia. By concentrating on the core pillars of data-driven research, academic publishing, and funding acquisition, this program provides a structured pathway for students to advance confidently in the competitive landscape of data science and AI research.

Additional Notes: Why Choose Our Program

  • Practical Outcomes: Participants will publish two research papers, enhancing academic credibility.
  • Skill Development: Training in academic writing, scholarship applications, and visa preparation.
  • Mentorship Connections: Establish long-term relationships with mentors for future growth.
  • Tool Mastery: Gain proficiency in data analysis tools such as R and Python.
  • Certification: Receive a certificate of participation upon program completion.

This program is designed to support participants at each stage of their research journey. It provides the tools, mentorship, and hands-on experience necessary for a successful academic career in data science.

Invited Lecturers

Confirmed Instructors

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Professor David Banks - USA

David Banks is a renowned statistician with an M.S. in Applied Mathematics and a Ph.D. in Statistics from Virginia Tech. He has held key roles in academia, government, and industry, including positions at Carnegie Mellon, NIST, FDA, and Duke University. Banks has led groundbreaking research programs at SAMSI and the Isaac Newton Institute, authored over 100 publications, and edited multiple books. A past president of the Classification Society and the International Society for Business and Industrial Statistics, he is a fellow of ASA, IMS, and AAAS. His research spans dynamic networks, adversarial risk analysis, human rights statistics, and high-dimensional data.

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Professor Olawale Awe

Olushina Olawale Awe is a distinguished statistician, data scientist, and professor with over 15 years of global experience spanning the public, private, and academic sectors. As Vice-President of Global Statistical Engagements for the USAID-funded LISA 2020 Network, he has spearheaded data science capacity-building initiatives across 35 centers in 10 developing countries. He founded Africa’s first LISA Statistics and Data Science Laboratory and has mentored numerous organizations worldwide. An accomplished scholar, he has published over 90 research articles and co-authored Promoting Statistical Practice and Collaboration in Developing Countries. Awe is a dynamic leader passionate about advancing statistical literacy globally.

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Professor Eric Vance – USA

Professor Eric Vance is the Director of the Laboratory for Interdisciplinary Statistical Analysis (LISA) at CU Boulder. He is dedicated to training statisticians and data scientists to excel as interdisciplinary collaborators, fostering meaningful partnerships across diverse fields. Under his leadership, LISA provides expert statistical collaboration to local researchers and actively engages with the community to enhance statistical skills and literacy on a broad scale.

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Paulo Canas Rodrigues

Paulo Canas Rodrigues, a distinguished statistician with a Ph.D. in Statistics (2012) from Nova University of Lisbon and Habilitation in Mathematics specializing in Statistics and Stochastic Processes (2019) from Instituto Superior Técnico, University of Lisbon, serves as a Professor at the Federal University of Bahia, Brazil, and has held key leadership roles, including President of ISBIS, Research Director of CAST, and editorial positions in multiple statistical journals, while contributing over 90 scientific papers, 140 invited talks, and significant research in statistical learning, time series forecasting, robust statistics, and big data analytics, with collaborations across 24 countries.

Professor DENNIS MURIITHI-

Prof. Dennis K. Muriithi is an accomplished Associate Professor in the Faculty of Science and Technology at the Chuka University, Kenya. He is a dedicated educator, accomplished researcher, and a recognized expert in the field of Applied Statistics and data analytics. Prof. Muriithi is dedicated to advancing scientific knowledge, mentoring future scientists, and promoting interdisciplinary research. His work focuses on Applied Statistics and data analytics: Machine Learning and Predictive Inference with application to Agriculture, Education, Health science and economic studies. He actively collaborates with both academic and industry partners to address real-world challenges using statistical tools.

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Dr. Deborah Awe

Dr. Deborah Awe is a dynamic medical professional with over 15 years of experience in patient care and transformative medical research. Her expertise spans maternal, neonatal, child, and adolescent health, machine learning, clinical trials, and bioethics. After earning her medical degree from the University of Ibadan, Nigeria, she pursued a master’s in Medical Statistics at the University of Nairobi, Kenya. Currently, she is completing a PhD in Tocogynecology at UNICAMP, Brazil, focusing on integrating artificial intelligence into maternal and perinatal health. With a global outlook and a passion for data-driven healthcare innovation, Dr. Awe is redefining maternal care worldwide.

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Dr Kim Love

Dr. Kim Love is a statistical consultant and educator with a Ph.D. in Statistics from Virginia Tech. As the owner of K. R. Love Quantitative Consulting, she specializes in supporting clients across nursing, health sciences, forestry, agriculture, and natural resources. Formerly the Associate Director of the University of Georgia Statistical Consulting Center, she has assisted over 180 clients annually and trained graduate students in statistical consulting. Dr. Love’s expertise includes regression, mixed effects models, experimental design, and more. Passionate about demystifying statistics, she excels at making data approachable for those with limited statistical confidence.

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Dr. Emmanuel Atofarati

Dr. Emmanuel Atofarati is a distinguished mechanical engineer and researcher with expertise in thermo-fluid systems and innovative engineering solutions. He earned his Ph.D. in Mechanical Engineering from the University of Pretoria, where his research focused on advancing thermal management strategies in engineering applications. Currently, he serves as a postdoctoral researcher at the University of South Africa, contributing to cutting-edge studies in thermal-fluid systems. He holds a master’s degree in Mechanical Engineering from Obafemi Awolowo University, Ile-Ife, specializing in thermo-fluid systems. Notably, he pioneered Nigeria's first indigenous thermal power plant, featuring an innovative indigenous steam turbine, earning national recognition and a government-awarded patent. He is proficient in CFD (ANSYS Fluent), CAD (SolidWorks), Python, Experimental data analysis and Machine learning.

Emmanuel Ola Ayeni

Emmanuel Ola Ayeni is a data enthusiast and consultant at Ada Global Concept with over eight years of experience in agile teams, including six years in distributed settings, leveraging expertise in Python, SQL, Unix, cloud computing, and machine learning to manage and transform large datasets, deploy predictive models, and drive data-driven decisions while seeking new challenges to expand his skills in the evolving tech landscape.

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Ayorinde Emmanuel Olatunde

Education: B.S. Statistics, Obafemi Awolowo University (Nigeria) M.S. Statistics, Kyungpook National University (South Korea) PhD Student in Applied Mathematics, CWRU MDS3 Research Areas: Uncertainty Quantification, Information Theory, Advanced Manufacturing, Study Protocol, Interdigitated Combs Background: As a PhD student in Applied Mathematics with a background in Statistics, Ayorinde is currently researching with MDS3, focusing on Uncertainty Quantification & Information Theory and extensions to other topical areas where statistical solutions for Material Data Science problems are needed. While collaborating with other field experts, he employs statistical methodologies and machine learning to optimize processes and contribute to interdisciplinary research initiatives.

Tolulope Adedoyin Oladeji

Tolulope Adedoyin Oladeji is an Environmental Health Scientist, Geospatial Data Analyst, and AI Researcher at the University of Cincinnati. With expertise in environmental analysis, modeling, and geospatial applications, he has published research on macroinvertebrate ecology, freshwater conservation, heavy metal bioaccumulation, and machine learning applications. His work addresses critical environmental challenges, focusing on biodiversity, water quality, and sustainable development in Nigeria and beyond.

Faustus Domebale Maale

My name is Faustus Maale, and I am a statistician and Data Scientist hailing from the vibrant country of Ghana in West Africa. My academic journey began at the Kwame Nkrumah University of Science and Technology, where I earned my bachelor’s degree in Statistics from 2017 to 2021. My thirst for knowledge led me to pursue a Master’s degree in Data Science at the Africa Institute for Mathematical Sciences in Cameroon, a journey made possible by a full scholarship from the Master Card Foundation Scholarship. This intensive 10-month program, culminating in a thesis, honed my skills and prepared me for the challenges ahead.

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Joshua Salako

Joshua Salako is an Innovative AI/ML Engineer merging electrical engineering foundations with 5+ years of software development expertise. Proven track record in developing scalable solutions using Python, TensorFlow, PyTorch, and Keras to drive business growth and user engagement. Combines strong mathematical background with hands-on experience in crafting efficient algorithms and collaborating across teams. Committed to leveraging cutting-edge technology for meaningful impact while staying current with emerging industry trends.

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Goodness Opateye

Goodness Opateye is a skilled Data Scientist, Data Analyst, and Machine Learning Researcher with extensive experience in data analysis, visualization, and education. Currently pursuing a Master’s degree in Artificial Intelligence, he leverages expertise in Python, SQL, and Scikit-Learn to deliver impactful insights and solutions. With a strong background in database management and instructional roles, Goodness excels in research, problem-solving, and fostering learning. Passionate about innovation, he is committed to advancing knowledge and driving meaningful change through data-driven strategies.

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Babatunde Adedeji

Babatunde Adedeji is a dedicated and accomplished professional with expertise in data analytics, chemical engineering, and research, currently driving efficient operations as a Data Analyst at IHS Towers. With a solid academic foundation in Chemical Engineering from Obafemi Awolowo University, where he graduated with an impressive GPA of 4.19/5.00, Babatunde combines technical proficiency in Microsoft Excel, Python, and SQL with a passion for advancing sustainability, energy, and environmental solutions. His diverse experience includes roles in process engineering and network surveillance, complemented by certifications in Data Science and Analytics. Babatunde is committed to leveraging data-driven insights to inform strategic decisions and create impactful solutions.

Sally Ndikum

Sally is a research assistant at the University of North Carolina at Charlotte, specializing in Geotechnical Engineering. Her current projects focus on analyzing and addressing cracks in road pavements, integrating innovative techniques to enhance pavement durability. With a background in data science and extensive professional experience in geotechnical engineering and construction project management, she brings a unique interdisciplinary approach to her work.

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Linkedin

Oluwafemi Abiona

Oluwafemi Abiona is a Data Analyst at ABInBev and a certified Microsoft Data Analyst with over four years of experience in data analytics, specializing in gathering, analyzing, and visualizing data for actionable insights. He holds a B.Sc. in Mathematics and a Data Analyst Nanodegree from Udacity, and has worked across diverse sectors, including finance, logistics, education, health, and energy. His career journey includes roles as a Machine Learning Intern, Data Analyst, and Data Scientist, where he led impactful projects like predictive models and market research. Oluwafemi is skilled in statistical modeling, machine learning, and predictive analytics, with notable achievements in top data science competitions. His technical expertise includes Python, SQL, Power BI, and machine learning libraries, which he uses to drive business growth and optimize operational performance across industries.

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Anthoria Njoku -  Canada

Anthonia Njoku is a dedicated PhD student in Computer Software Engineering at Polytechnique Montréal, specializing in MLOps and machine learning. She focuses on creating seamless transitions for machine learning models from research to production, optimizing business prediction and analytics. With a solid academic background in data science from the African Institute for Mathematical Sciences (AIMS), Anthonia is skilled in Python, machine learning, data analysis, and DevOps. Her diverse experience spans research, internships, and program management, reflecting her passion for leveraging technology to solve complex challenges.

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John Solomon

John solomon is a passionate and versatile Data Scientist and Software Developer with expertise in Data Science technologies, Django, and full-stack development. Adept at leveraging software development skills and advanced data analytics to build innovative solutions that solve real-world problems. Committed to staying at the forefront of technology trends to deliver impactful and efficient results.

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Olawale Olaniyan

Olawale Olaniyan an experienced data science and statistics professional with a strong foundation in biostatistics, machine learning, and predictive analytics, having worked with tools like Python, R, and SAS, and gained hands-on experience through internships and research projects in healthcare and public health, with a passion for transforming data into actionable insights and contributing to data-driven decision-making.

Jacob Ojumu

Jacob Ojumu is a Data Scientist with extensive experience in extracting meaningful insights from complex datasets, specializing in predictive modeling and statistical analysis. Through his career, he has demonstrated exceptional prowess in transforming raw data into actionable business solutions. As a passionate data science and analytics trainer, he has empowered numerous individuals with the skills needed to navigate the field of data science, focusing on practical applications and industry practices. His research interests lie at the intersection of data science and critical global challenges, particularly in environmental sustainability, public health initiatives, and agriculture. By leveraging artificial intelligence, he strives to develop innovative solutions that address pressing issues in these sectors

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Dr. Jeremiah Adepoju

Dr. Jeremiah Adepoju is an accomplished Machine Learning Scientist and Data Engineer with a proven track record of excellence in artificial intelligence and data-centric governance. Currently contributing to groundbreaking projects at MLCommons, he leverages his expertise to advance the development of machine learning benchmarks and systems. Dr. Adepoju is also an active community member at leading AI organizations, including Alignment Labs AI, EleutherAI, Nous Research, and ML Collective, where he collaborates on innovative solutions for real-world problems. Dr. Adepoju's technical acumen spans across machine learning, data engineering, and software development. He has honed his skills in Python programming, natural language processing, neural networks, and deep learning through advanced training programs at MuzeData and DLYA. His expertise includes working with SQL databases, data visualization tools such as matplotlib and seaborn, and interactive visualization platforms like Plotly.

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Linkedin

Adeyemo Barnabas

Adeyemo Barnabas is a graduate of Materials Science and Engineering from Obafemi Awolowo University, currently working as a research officer in a reputable institution. He is passionate about carrying out academic research with applications in Data Science and Machine Learning. Leveraging on insights obtained from attending conferences, some of which were organized by Microsoft Inc. on Responsible Artificial Intelligence, and AWS on Innovation and Security in the Cloud, amidst others, he volunteers in Tech communities to train individuals on the use of Python for Data Science. He has an extensive experience in using LATEX for writing research papers. He is an enthusiastic trainer who offers a wholesome educative experience for learners.

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Professor Ahmad Zahoor

Professor Ahmad Zahoor is an accomplished academic and researcher in the field of chemistry, serving as an Associate Professor at the University of Engineering and Technology (UET) Lahore, Pakistan. He holds academic credentials from prestigious institutions, including the University of Engineering and Technology, Lahore, and Quaid-e-Azam University, Islamabad. With a strong commitment to advancing chemical research and education, Professor Zahoor has contributed significantly to the academic community through teaching, research, and scholarly publications. His expertise and dedication have made him a respected figure in the fields of chemical sciences and higher education in Pakistan.