Data Science and Analytics In
Big Data Essentials
This Big Data Essentials course is designed to introduce students to the fundamental concepts and technologies of big data, including data processing, storage, and analytics. Students will learn about the challenges of big data, the Hadoop ecosystem, and popular big data tools such as Apache Spark, Hive, and Pig.
Overview
Big Data Essentials
Course Learning Outcomes (CLOs) and SLOs
Course Learning Outcomes (CLOs) typically include:
Student Learning Outcomes (SLOs) are specific goals for students, such as:
Benefits
With AI, the world is your oyster! It is an emerging field, rapidly growing, ever evolving and watched with a keen eye by industries and markets globally. There are many benefits to an education in AI:
In demand Career
With a Bachelor in artificial intelligence you are equipped with in-demand skills in the rapidly growing field of AI. Knowledge of developing AI systems, data analysis and AI techniques makes you valuable across industries, right from healthcare, finance, tech and more. This degree prepares you for career that has multiple options for diversification. AI professionals include AI engineers, data scientists, machine learning specialists, AI consultants, researchers and more. AI is transformative technology that is revolutionising the world. With an education background in AI, you are set up in an in-demand career field with an exciting future ahead!
Innovation and advancement
Applied AI is all about finding solutions and using AI systems to make life simpler. Applied AI draws on its solid foundation in Computer Science to analyse and provide solutions for real world challenges. You are prepared to address complex problems and contribute meaningfully in domains like healthcare diagnostics, fraud detection, autonomous vehicles, personalised recommendations and more. Being able to apply AI techniques for solving tasks makes for an extremely rewarding and impactful job role!
Solving real world problems
AI aims to constantly bridge the gap between natural intelligence and machine learning - it is a field of cutting edge research, innovation and advancing technology. This makes it ever evolving, with new algorithms, models and techniques being developed. By studying AI at an undergraduate level, you gain a strong foundation in AI fundamentals that help you better understand the latest advancements. You step into a career that empowers you to push the boundaries of AI, contribute to research and development and drive innovation in the field.
100% International
Study at your own pace from anywhere in the world
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50,000+ students
enrolled in Germany’s largest university
Study contents
Contents
Big Data Essentials Short Course Outline
1. Introduction to Big Data
2. Big Data Technologies and Tools
3. Data Storage and Management
4. Data Processing and Analysis
5. Data Governance and Security
6. Case Studies and Applications
7. Future Trends in Big Data
8. Hands-on Labs and Projects
9. Conclusion and Certification
Target Audience
This outline provides a structured approach to cover essential aspects of big data, ensuring participants gain both theoretical knowledge and practical skills necessary to work effectively in a big data environment.
Admission
Admission Criteria
Education: Bachelor's degree in a related field such as Computer Science, Information Technology, Data Science, or Mathematics. Some programs may accept students with a non-technical background, but they may require additional coursework or certifications. Work Experience: Typically, 1-3 years of experience in a related field such as data analysis, data science, or IT. Prior experience with big data technologies such as Hadoop, Spark, or NoSQL databases is desirable. Skills: Programming skills in languages such as Python, Java, or R. Familiarity with data analytics and visualization tools such as Tableau, Power BI, or D3.js. Understanding of data structures, algorithms, and statistical concepts. Knowledge of big data technologies such as Hadoop, Spark, NoSQL databases, and cloud computing platforms. Certifications: Some programs may require or recommend certifications such as: Certified Data Scientist (CDS) or Certified Analytics Professional (CAP) from the International Institute for Analytics (IIA). Certified Big Data Developer (CBDD) or Certified Big Data Engineer (CBDE) from the Data Science Council of America (DSCA). Admission Test Scores: GRE or GMAT scores may be required for some programs. TOEFL or IELTS scores may be required for international students. Recommendations: Typically, 1-2 letters of recommendation from academic or professional references. Personal Statement: A written statement outlining your motivation for pursuing a career in big data and your goals for the program. Portfolio: Some programs may require a portfolio of your previous work or projects that demonstrate your skills in data analysis and visualization. Interviews: Some programs may include an interview as part of the admission process to assess your communication and problem-solving skills.
Careers
Find your Career now
Data Scientist: Responsible for extracting insights and knowledge from large datasets using various techniques such as machine learning, statistical modeling, and data visualization. Business Intelligence Developer: Designs and develops business intelligence solutions to analyze and visualize data, providing insights to help organizations make informed business decisions. Data Engineer: Develops and maintains the infrastructure and systems that store, process, and retrieve large datasets, ensuring data quality, security, and scalability. Data Analyst: Analyzes and interprets data to identify trends, patterns, and correlations, providing insights to help organizations make informed business decisions. Data Architect: Designs and implements the overall data architecture, ensuring data consistency, scalability, and security across an organization. Machine Learning Engineer: Develops and deploys machine learning models to solve complex problems, such as predictive modeling, natural language processing, and computer vision. Data Quality Specialist: Ensures the quality of data by identifying errors, inconsistencies, and inaccuracies, and developing processes to correct them. Business Analyst: Works with stakeholders to understand business needs and develops data-driven solutions to solve problems and improve business operations. Predictive Modeling Specialist: Develops predictive models using statistical and machine learning techniques to forecast future outcomes and optimize business decisions. Data Visualization Specialist: Creates interactive dashboards, reports, and visualizations to help organizations understand complex data insights. Cloud Data Engineer: Designs and develops cloud-based data architectures, including storage, processing, and analytics solutions. Data Governance Specialist: Develops policies, procedures, and standards for data management, ensuring compliance with regulatory requirements. Machine Learning Researcher: Conducts research in machine learning algorithms and applications to develop new solutions for various industries. Big Data Developer: Develops software applications that can handle large datasets using big data technologies such as Hadoop, Spark, and NoSQL databases. Data Security Specialist: Ensures the security of sensitive data by implementing encryption, access controls, and monitoring systems.
Student reviews
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Tuition fees
Big Data Essentials (Duration 4 Weeks)
350 $
200 $ / Total CostAll our study programmes include the following benefits
- Teaching and study material
- Marking of your end-of-module exams
- Monthly live and recorded tutorials
- Use of the online campus
- Individual study coaching
- Online exams
- Career coaching
- Learn English for free
Our global recognition
IU is recognised by WES Canada and U.S., which means your degree can be converted to points in the local system for purposes of immigration, work, or studies.
As the first EU institution in UNESCO's Global Education Coalition, IU is committed to ensuring accessible quality education to students in crisis worldwide through free online micro-credentials.
Our company partners
For over 20 years, IU has established partnerships with leading global companies. This offers you the chance to gain firsthand experience through internships and projects and allow us to adapt our learning content to the ever-evolving needs of the labour market. You'll benefit from an education designed to bridge the gap between theory and real-world practice, ensuring your readiness for your future career.
Recognition
Recognition of previous achievements
Have you already completed a training course, studied at a university or gained work experience? Have you completed a course or a learning path through EPIBM LinkedIn Learning, and earned a certificate? Then you have the opportunity to get your previous achievements recognised, and complete your studies at EPIBM sooner.
Save time:
Skip individual modules or whole semesters!
Even before you apply for a study programme, we’ll gladly check whether we can take your previous achievements into account: 100% online, no strings attached. Simply fill in our recognition application form, which you can find under the content section of each study programme's webpage, and upload it via our upload section. You can also e-mail it to us, or send it via post.
Send an email to [email protected] to find out which previous achievements you can get recognised. You can get your previous achievements recognised during your studies.
Recognition files
Autonomous vehicles developer
With AI, the world is your oyster! It is an emerging field, rapidly growing, ever evolving and watched with a keen eye by industries and markets globally. There are many benefits to an education in AI:
That’s why after graduating, you’ll be able to apply your professional skills and knowledge, and work for development teams at any sector you find appealing.
Augmented reality (AR/VR) developer
Virtual (or augmented) reality isn’t all just fun and games, as great and enjoyable as that aspect is. It can also be used for groundbreaking social and psychological research, defensive purposes and therapy.
With an Applied Artificial Intelligence degree from IU University of Applied Sciences, you can take part in this vital field of technological development, and work on a wide variety of interesting projects.
Change what the world thinks about the possibilities that AI offers, and make a real difference in people’s lives, while enjoying every step of the process.
F.A.Q
Frequently Asked Questions
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