Nex-G Innovations

Training is focused on use cases in each IoT vertical (Wearables, Healthcare, Manufacturing, Retail, Supply chain, Smart energy, Smart cities, Smart Home, Connected Cars) and solutions using algorithms based on data, build models and predictions (machine learning).

Code: NES_SK_1751

Duration: 4 Weeks / 40 Hrs / Customized

Mode: Online / Offline / Onsite

+91-8826900551

• What is Data Science? What problems can be solved using Data science - Extracting meaning from Data - Statistical processes behind Data - Techniques to acquire data (ex APIs) - Handling large scale data - Big Data fundamentals

Hadoop Fundamentals

• Introduction to the Hadoop ecosystem - SQL NoSQL

Data Science and IoT

• The IoT ecosystem
• Unique considerations for the IoT ecosystem - Addressing IoT problems in Data science (time series data, enterprise IoT edge computing, real-time processing, cognitive computing, image processing, introduction to deep learning algorithms, geospatial analysis for IoT/managing massive geographic scale, strategies for integration with hardware, sensor fusion)

IoT datasets

• An exploration of IoT datasets and APIs by application: Healthcare
• Manufacturing
• wearables
• Energy Connected Cars etc

Developing for IoT devices

• Design and development of a typical IoT solution from the perspective of the flow of Data

Mathematical foundations of Machine Learning algorithms

• Linear Algebra including Matrix algebra
• Bayesian Statistics
• Optimization techniques (such as Gradient descent) etc

Machine Learning techniques and algorithms

• Supervised algorithms
• unsupervised algorithms (classification, regression, clustering, dimensionality reduction etc).

Python Programming

• In this phase, we use our Python based platform and a unique methodology. We use Python based tools and libraries like the iPython notebook
• the Anaconda distribution
• sci-kit learn
• Pandas and Wakari

Platforms and Projects

• Design and development of sample project using above skills. Here, you work with specific commercial platforms (MapR, MongoDB etc) and IoT related projects. We use the platforms like MapR to study the evolution of Hadoop as applicable to IoT (stream processing, in-memory processing, Spark, Storm and its variants beyond map reduce) and SQL. In this phase, we work with projects based on the platforms