International Conference on Big Data and ML-driven IT Innovation Strategies

ICBDMLITIS

18th Sep – 19th Sep 2026 Abuja, Nigeria

Official Invitation Letter Available

An official invitation letter will be provided upon successful registration for your participation in the conference.

Benefits of Registering as Listener

Access to All Conference Sessions

Plenary, keynote and parallel sessions

Networking Opportunities

Connect with global educators & researchers

Certificate of Participation

Digital certificate of participation

Invitation Letter Support

Official invitation letter after successful registration

Conference Kit / Digital Materials

E-proceedings & resource materials

Access to Keynote Sessions

Learn from leading experts & scholars

Credit Card

Debit Card

Net Banking

Cash Card

Unified Payments

Select Registration Mode

Standard / Physical Participation USD

Join us on-site for keynotes, talks, workshops, networking, conference kit and certificate.

Virtual Participation USD

Participate online via live streaming. Includes live access to all sessions, digital materials and certificate.

Participant Details

Full Name *

Email Address *

Mobile Number with Country Code *

City *

State *

Country *

Zip / Postal Code *

Address *

Coupon Code

10% OFF on Registration.
Use Coupon Code → EARLY10

Terms & Condition

I agree to the Terms & Conditions and Refund & Cancellation Policy.

Registration Summary

Conference ICBDMLITIS

Date 18th Sep – 19th Sep 2026

Location Abuja, Nigeria

Participation Type Listener

Organizer Science Leagues

Registration Mode Standard / Physical

Registration Fee USD 0.00

Bank Convenience Charges (5.8%)i USD 0.00

Calculated based on 5.8% of the registration fee

Discount USD 0.00

Total Payable USD 0.00

100% Secure Payment

Your payment information is encrypted and processed securely.

Conference Session Tracks

Aligned with UN Sustainable Development Goals

The conference's session tracks effectively support the following SDGs.

01 Innovative Applications of Big Data in Engineering +

This track explores the transformative applications of big data within engineering disciplines. It focuses on case studies and methodologies that leverage big data for enhanced decision-making and operational efficiency.

SDG 9 SDG 12

02 Machine Learning Techniques for Predictive Analytics +

This session delves into advanced machine learning algorithms and their applications in predictive analytics. Participants will discuss the effectiveness of various models in forecasting trends and optimizing processes.

SDG 8 SDG 9

03 Cloud Computing Solutions for Scalable IT Infrastructure +

This track examines the role of cloud computing in developing scalable IT infrastructures. It highlights innovative strategies for leveraging cloud technologies to enhance data storage, processing, and accessibility.

SDG 9 SDG 11

04 Intelligent Systems and Automation in Engineering +

This session focuses on the integration of intelligent systems and automation in engineering practices. It aims to showcase advancements that improve efficiency, accuracy, and safety in engineering operations.

SDG 8 SDG 9

05 Data Analytics Frameworks for Business Intelligence +

This track investigates various data analytics frameworks that support business intelligence initiatives. Participants will explore how these frameworks can be utilized to derive actionable insights from large datasets.

SDG 8 SDG 9

06 AI Algorithms for Enhanced Decision-Making +

This session highlights the application of artificial intelligence algorithms in decision-making processes. It emphasizes the importance of AI in improving the quality and speed of engineering decisions.

SDG 9 SDG 16

07 System Optimization Techniques in IT Infrastructure +

This track focuses on innovative techniques for optimizing IT infrastructure systems. Discussions will center on methodologies that enhance performance, reduce costs, and improve reliability.

SDG 9 SDG 12

08 Big Data Analytics in Smart Manufacturing +

This session explores the application of big data analytics in the context of smart manufacturing. It aims to highlight how data-driven insights can lead to improved production processes and product quality.

SDG 9 SDG 12

09 Challenges and Solutions in Machine Learning Deployment +

This track addresses the challenges faced during the deployment of machine learning models in real-world applications. Participants will discuss best practices and innovative solutions to overcome these obstacles.

SDG 9 SDG 16

10 Data-Driven Strategies for IT Innovation +

This session examines how data-driven strategies can foster innovation in IT. It focuses on the intersection of data analytics and IT development to drive forward-thinking solutions.

SDG 9 SDG 12

11 Future Trends in Big Data and Machine Learning +

This track looks ahead to future trends in big data and machine learning technologies. Participants will explore emerging technologies and their potential impact on engineering and IT innovation.

SDG 9 SDG 12