Machine Learning for Big Data
( 24 Modules )

Module #1
Introduction to Big Data
Overview of big data, its characteristics, and importance

Module #2
Introduction to Machine Learning
Overview of machine learning, its types, and applications

Module #3
Big Data Storage and Processing
Review of big data storage options (HDFS, NoSQL, etc.) and processing frameworks (MapReduce, Spark, etc.)

Module #4
Machine Learning for Big Data:Challenges and Opportunities
Discussion of the challenges and opportunities of applying machine learning to big data

Module #5
Data Preprocessing and Feature Engineering
Best practices for preprocessing and feature engineering in big data sets

Module #6
Supervised Learning Fundamentals
Overview of supervised learning concepts, including regression, classification, and model evaluation

Module #7
Scalable Supervised Learning with Spark MLlib
Hands-on experience with Spark MLlib for supervised learning on big data

Module #8
Unsupervised Learning Fundamentals
Overview of unsupervised learning concepts, including clustering, dimensionality reduction, and density estimation

Module #9
Scalable Unsupervised Learning with Spark MLlib
Hands-on experience with Spark MLlib for unsupervised learning on big data

Module #10
Deep Learning Fundamentals
Overview of deep learning concepts, including neural networks, convolutional networks, and recurrent networks

Module #11
Scalable Deep Learning with TensorFlow and Spark
Hands-on experience with TensorFlow and Spark for deep learning on big data

Module #12
Model Evaluation and Hyperparameter Tuning
Best practices for model evaluation and hyperparameter tuning in machine learning

Module #13
Big Data Visualization and Interpretability
Techniques for visualizing and interpreting machine learning models on big data

Module #14
Distributed Machine Learning with Apache Spark
In-depth exploration of Sparks distributed machine learning capabilities

Module #15
Machine Learning on NoSQL Databases
Hands-on experience with machine learning on NoSQL databases such as MongoDB and Cassandra

Module #16
Real-time Machine Learning with Apache Flink
In-depth exploration of Apache Flinks real-time machine learning capabilities

Module #17
Machine Learning on Streaming Data
Techniques for applying machine learning to streaming data from sources like IoT sensors and social media

Module #18
Machine Learning for Recommendation Systems
Best practices for building recommendation systems using machine learning on big data

Module #19
Machine Learning for Natural Language Processing
Applications of machine learning to natural language processing on big data

Module #20
Machine Learning for Computer Vision
Applications of machine learning to computer vision on big data

Module #21
Case Studies in Machine Learning for Big Data
Real-world case studies of machine learning applications on big data

Module #22
Big Data Machine Learning Project Development
Hands-on experience with developing a machine learning project on big data

Module #23
Machine Learning on Cloud-Based Big Data Platforms
Overview of machine learning on cloud-based big data platforms such as AWS, GCP, and Azure

Module #24
Course Wrap-Up & Conclusion
Planning next steps in Machine Learning for Big Data career

WIZAPE

ONLINE RESOURCES

ABOUT WIZAPE

ONLINE PORTAL

Our priority is to cultivate a vibrant community before considering the release of a token. By focusing on engagement and support, we can create a solid foundation for sustainable growth. Let’s build this together!

We're giving our website a fresh new look and feel! 🎉 Stay tuned as we work behind the scenes to enhance your experience.
Get ready for a revamped site that’s sleeker, and packed with new features. Thank you for your patience. Great things are coming!

CONTACT-US PRIVACY POLICY

Machine Learning for Big Data ( 24 Modules )

Machine Learning for Big Data
( 24 Modules )