Big Data Analytics Course








Big Data Analytics certification course
What will I learn?
- Learn the fundamentals of distributed computing and parallel processing.
- Learn advanced analytics techniques including machine learning and predictive modeling.
- Understand real-world applications of big data analytics across various industries.
- Develop skills in visualizing and communicating insights derived from big data.
- Understand the concepts and challenges of big data analytics.
- Master techniques for data cleaning, transformation, and preprocessing in big data environments.
- Develop skills in teamwork, communication, and problem-solving to collaborate effectively with multidisciplinary teams.
- Explore machine learning algorithms such as regression, classification, clustering, and recommendation systems for predictive analytics.
- Explore real-world applications across industries such as healthcare, finance, retail, and telecommunications.
Requirements
- Basic understanding of statistics and data analysis concepts.
- No prior experience with big data technologies is necessary.
Big Data Analytics Course Content
- Basics of big data and its key traits
- Understanding Volume, Velocity, Variety, Veracity
- Importance and uses of big data in industries
Gathering and sourcing data
Cleaning, transforming, and integrating data
Storage options: SQL, NoSQL, Hadoop, and cloud platforms
- Summarizing and exploring datasets
- Visualizing data with charts, dashboards, and graphs
- Tools like Tableau, Power BI, matplotlib, and seaborn
- Overview of Hadoop components: HDFS, MapReduce, YARN
- Working with Apache Spark: SQL, Streaming, MLlib
- Introduction to Hive, Pig, and similar frameworks
- Basics of machine learning models
- Techniques in supervised and unsupervised learning
- Algorithms for large-scale and real-time data
Predictive modeling and trend forecasting
Text mining, NLP, and social media analytics
Analyzing patterns in time-based data
Key security challenges in big data
Encryption, access control, and compliance standards
Privacy frameworks like GDPR and CCPA
Big data applications in finance, healthcare, and retail
Practical projects on analyzing large datasets
Group activities to address industry-based problems
Managing bias, privacy, and transparency in analytics
Legal aspects: data rights, regulations, and IP laws
- Analytics at the edge and IoT integration
- Deep learning for massive datasets
- Blockchain’s role in secure data management
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Why Choose Big Data Analytics Certification Course from Bright Computer Education?

Designed Curriculum
Our curriculum covers everything from basic to advanced topics. Topics include variables, data types, control structures, functions, OOP, STL, and more.

Hands-on Learning
Dive into practical exercises and coding projects that reinforce learning and help you build real-world applications.

Experienced Instructors
Learn from industry experts with years of experience in C programming and software development.

Flexible Learning
Choose from flexible scheduling options, including self-paced learning or live virtual classes to fit your busy lifestyle.

Career Development
Gain valuable skills sought after by employers in various industries, from software development to embedded systems and beyond.

Interactive Learning
Engage with fellow learners and instructors through live Q&A sessions, discussion forums, and collaborative coding exercises.
Diverse Career in Big Data Analytics: Exploring Paths in India's Technology Sector
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