Use the discount code BF30 at checkout get 30%off a selection of courses in our IBM expert series.
What you get in the series deal
If you want to join a new wave of data-savvy professionals, whilst gaining an IBM certified qualification, explore our data science series. Get started with our foundation course. Or go for something more challenging with intermediate or advanced.
**Use the discount code BF30 at checkout get 30% off.**
Understand how data science supports the digital transformation of business.
Get acquainted with the roles of a Data science team.
Access Data science collaboration platforms in the cloud.
Internalise the data science methodology.
Construct usable data sets by identifying and collecting the data required.
Hands-on experience with IBM Watson Studio, Data Refinery Spark, Jupyter Notebooks.
Understand the use of AI automation to accelerate the data model management lifecycle.
Understand linear algebra principles for machine learning.
Understand the relevance of data science projects in supporting the digital transformation of business across multiple industries. Get acquainted with the following roles of a data science team: Data Scientist, Data Engineer, Data Analyst and AI Developer.
2. Data Science on the Cloud
Access data science collaboration platforms in the cloud, including IBM Watson Studio and Data Refinery.
Level 2 – Data Science Tools
3. Watson Studio Data Refinery Visualisations
Acquire a data science cross-disciplinary skillset found at the intersection of statistics, computer programming and domain expertise by experimenting with data ingestion and manipulation using a CSV dataset.
Explore people, process and tools required to build an effective data science team.
2. Data Science on the Cloud
Understand the key statistics, concepts and methods essential to finding structure in data and making predictions.
3. Data Science Methodology
Internalise the data science methodology by learning to: Characterise a business problem, Formulate a hypothesis, Demonstrate the use of methodologies in the analytics cycle and Plan for execution
Level 2 – Data Wrangling
4. Explore and Prepare Data
Construct usable data sets by identifying and collecting the data required for different scenarios within your organisation.
5. Explore Insurance Claim Data
Explore an insurance industry scenario leveraging cutting-edge fraud analytics approaches and technologies. You will explore car insurance claims data and prepare insurance claims data for analysis. You’ll also get hands-on experience with Watson Studio, working with the Refinery and Data Visualisation tools to perform data wrangling tasks.
6. Represent and Transform Data
Manipulate, transform and clean the data you have constructed in previous modules. Demonstrate the ability to deal with data anomalies such as missing values, outliers, unbalanced data and data normalisation.
7. Discover Patterns in Claims Fraud
You will complete the methodological approach as a data scientist, transforming data and finding fraud patterns with data representation. You’ll also get hands-on experience with Watson Studio, working with the Refinery and Data Visualisation tools to perform additional data wrangling tasks.
Level 3 – Decision Support
8. Data Visualisation and Presentation
Explore the concepts of decision-centred visualisation and understand how data journalists use a variety of tools and graphs to help decision makers, looking at the purpose, audience, data and context of a human-centred reflection. Explore the fundamentals of visualisations and avoid “tricky” situations and understand and interpret graphs from different perspectives.
9. Fraud Diagnostic Analysis
Explore data from different perspectives and visualisations to help you to identify patterns, connections and relationships within data. You will access IBM Cloud and provision the Watson Studio Service to cleanse, analyse and reshape claims data, run summary statistics on the results and then validate the insurance claims data.
1. Data Modelling Understand different modelling techniques, model variation and selection techniques. Depending on your current level of expertise, a thorough understanding of these concepts may require additional self-study on advanced statistical methods and algorithms.
2. Machine Learning Algorithms Learn about advanced data analytics through the adoption of Machine Learning. Depending on your current level of expertise, a thorough understanding of these concepts may require additional self-study on advanced statistical methods and algorithms.
Level 2 – AI Data Science Automation
3. Predict Fraud Using AutoAI Demonstrate advanced skill application in the field of data science by role-playing critical roles in a data science team using latest AI tools such as AutoAI for analytics or automation to address real problems. Involves an interactive case study.
4. Fraud Detection Using Visual Recognition Gain hands-on experience in IBM Watson Visual Recognition, understanding the inner dynamics of an auto insurance company and use Data science and AI to improve business outcomes.
IBM is a leading cloud platform and cognitive solutions company. Restlessly reinventing since 1911, we are the largest technology and consulting employer in the world, with more than 350,000 employees serving clients in 170 countries. With Watson, the AI platform for business, powered by data, we are building industry-based solutions to real-world problems. For more than seven decades, IBM Research has defined the future of information technology with more than 3,000 researchers in 12 labs located across six continents. For more information, visit ibm.com/this-is-ibm
Lead Data Scientist
Dylan is a Lead Data Scientist at IBM. He specialises in statistics, NLP, dynamic pricing, machine learning, and data exploration. He also has experience as a full stack web and mobile IOS developer. By using his experience in software engineering, he helps to bridge the gap in projects between developers and data scientists. Outside of work, he enjoys painting, reading, and learning to play the piano.
Customer Success Manager, Architect and Data Scientist
U.S Communications Computer Systems Integration market, IBM
Precious Chima is a Customer Success Manager, Architect & Data Scientist working within the U.S Communications Computer Systems Integration market at IBM. Before taking on this role, he was a member of the IBM Cloud Pak Acceleration Team, where he helped clients in multiple industries accelerate their Digital Transformation through Cloud Adoption. Precious' expertise lies within Machine Learning, Deep Learning, Big Data, and Microservices. He currently holds certification in TensorFlow Development, Apache Hadoop & Spark, and Red Hat OpenShift (Container & Kubernetes). Precious is passionate about building well-architected AI systems that are fair, smart, and secure. Before joining IBM, he worked in the Oil & Gas industry, where he specialised in parametric optimisations of drill bits to improve overall drilling performances. During his spare time, he enjoys exercising, reading, watching/playing basketball, and inventing.
Dr. Kaoutar El Maghraoui
Principal Research Scientist
IBM T.J Watson Research Center
Dr. Kaoutar El Maghraoui is a principal research scientist at the IBM T.J Watson Research Center where she is focusing on innovations at the intersection of systems and artificial intelligence (AI). She leads the research agenda of End-Use experimental AI testbed of the IBM Research AI Hardware Center, a global research hub focusing on enabling next generation accelerators and systems for AI workloads. She co-led IBM’s Global Technology Outlook in 2017 where she contributed to creating IBM’s vision for the future of IT across global labs and business units focusing on IBM’s AI leadership. Kaoutar has co-authored several patents, conference, and journal publications in the areas of systems research, distributed systems, high performance computing, and AI. Kaoutar holds a PhD. Degree from Rensselaer Polytechnic Institute, USA. She received several awards including the Robert McNaughton Award for best thesis in computer science, Best of IBM award in 2021, IBM’s Eminence and Excellence award for leadership in increasing Women’s presence in science and technology, several IBM outstanding technical accomplishments, and 2021 IEEE TCSVC Women in Service Computing award. Kaoutar is global vice-chair of the Arab Women in Computing organisation and avid supporter and volunteer of several women in science and technology initiatives.
Matt has work experience in logistics, eCommerce start-ups, and banking, focusing on analytics and data science. His expertise is in natural language processing, natural language understanding, and computer vision. Prior to IBM, he worked at a start-up providing insights to consumers through transparency into foods they are consuming.
Armen Pischdotchian - Academic Developer
IBM Corporation, Cambridge, MA
Armen is currently an Academic Developer at IBM Global University Programs. In this role, he drivesadoption of IBM technologies with faculty and students worldwide with the IBM Academic Initiativeand the IBM Skills Academy to grow skills in key technology areas including artificial intelligence,data science, cognitive security, blockchain and more. He is also lead course developer andinstructor for the artificial intelligence and data science curriculum for the Skills Academy offerings.
Armen is also an Adjunct Professor at Wentworth Institute of Technology in Boston. His eveningclasses includes topics on artificial intelligence, including statistical and mathematical constructs ofmachine learning algorithms; plus, data science doctrines using hands on labs using Python inJupyter Notebooks. The semester ends with an elaboration on Blockchain technologies as it relatesto consensus, provenance, immutability and finality.
Dr. Ray Lopez
Manager and Senior Curriculum Architect, IBM Data and AI Expert Labs Group
Dr. Ray Lopez is a Manager and the Senior Curriculum Architect for the IBM Data and AI Expert Labs group. In this role he manages a team of amazing data science experts who build educational content on the use of IBM Watson tools and APIs for data science tasks and infusing AI into enterprise processes.
Dr. Lopez has over 25 years of experience in software engineering, system administration, enterprise architecture, and consulting for a very wide variety of clients in the public and private sectors and has over 30 years of experience as a researcher and professor. He is a Professor of Practice at the University of Texas at San Antonio (Enrolment=34,000; Carnegie Classification R2, High Research Activity) where he teaches courses on statistics, research design, cognitive science, sensation and perception, and ethics. Dr. Lopez received his BA from the University of Texas at Austin, and MS and PhD from the University of Texas at Arlington, where his pioneering research on midbrain mechanisms of pain processing became the basis for many topic areas of pain research. Raised in rural south Texas, Dr. Lopez is the eldest of five siblings and very proud of his Mexican and Tejano heritage. He currently lives in San Antonio, Texas with his family and is an active volunteer for several organisations. In his spare time, he enjoys reading about history, science, and philosophy, playing chess, vintage computing, camping and hiking, and spending time with the family.
Once you enrol on the series, it's self-paced, so you can learn at your own speed and progress through the individual modules in a way that suits you. You will progress through them in order as the course is set up to constantly build your knowledge throughout.
After completing this course, you will receive an IBM Badge, awarded by the IBM Skills Academy. They are secure, web-enabled credentials that contain granular, verified information employers can use to evaluate an individual's potential. After completing the program, you'll receive your badge from UK Learns via email.
The courses are divided into practice levels. Each course covers more advanced topics and builds up on top of the concepts, practice and skills addressed on the previous levels. You will be your own guide on this course, using your current skillsets to navigate the learning modules on the course at your own pace.
After each module, you'll complete some knowledge check questions to ensure you have understood everything in the module.
- Foundation - This badge earner has completed all the learning activities included in this online learning experience, including hands-on experience, concepts, methods, and tools related to data science roles and their use of technology applied to enterprise projects. The individual has demonstrated knowledge and understanding of the foundations of Data science including data science team roles, data analysis tools, and real-world use cases for the application of the data science method.
- Intermediate - This badge earner has completed all the learning activities included in this online learning experience including hands-on labs, concepts, methods and tools related to the data science methodology. They demonstrate skills and understanding of the data science methodology by engaging in real-world scenarios and role-playing the process / tools used by a data science team; learning example: An insurance industry scenario leveraging cutting-edge fraud analytics approaches and technologies.
- Advanced - This earner completed all learning activities included in this online learning experience related to advanced topics core to the data science profession including Data modelling techniques; Machine learning; Deep learning algorithms; Data science automation; demonstration of advanced skills application in the field of Data Science by role-playing critical roles in a data science team using latest AI tools for analytics / automation to address real problems.
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