Course Objective
Prepare students to use the integration of Embedded Systems and Artificial Intelligence to resolve challenges in industrial systems. Students will learn how incorporating machine learning and deep learning algorithms with embedded systems can streamline processes and automate tasks. Focus will be on developing system approach through integrated projects to master specific methods and tools applied in the aeronautics, space, automobiles, and multimedia domains. The course will impart an in-depth knowledge focussing on both theoretical and practical aspects.
Fee Structure
The course comprises of 6 modules mentioned under the Course Syllabus below. Student can enrol for the full course (6 modules) or is free to enrol for individual modules.
Registration Fee: Rs.500/-
Full Course Fees: Rs.94500/-
Each Module Course Fees: Rs.17500/-
Registration fees and course fees
should to be paid online or by Demand Draft.
Online Payment Details: Account Name – ICIT PVT LTD
Account Number: 27205000514
IFSC Code: SCBL0036107
Bank: Standard Chartered Bank
Bank Branch: Aundh Branch, 163, Harsh Orchid, New DP Road, Nagras RoadMall, Ward no 8, Aundh, Pune 411007
Demand Draft: To be drawn on any nationalized bank in favour of “ICIT Pvt. Ltd., Pune” and should
be payable at par.
Note that registration and course fees once paid are non refundable.
Database Management Systems
- Introduction to Databases
- Database Design Principles
- SQL Syntax and Query Fundamentals
- Data Definition Language (DDL)
- Data Manipulation Language (DML)
- Data Control Language (DCL)
- Transaction Management
- Indexing and Optimization Techniques
- Normalization
- Entity-Relationship (ER) Model
- SQL Joins and Subqueries
- Stored Procedures and Functions
- Database Security
- Backup and Recovery Techniques
Exploratory Data Analysis
- Data Quality Assessment
- Handling Missing Values
- Data Filtering
- Outlier Detection
- Data Transformation
- Feature Scaling and Normalization
- Encoding Categorical Data
- Data Integration
- Date and Time Data Handling
- Dealing with Duplicate Data
- Using Regular Expressions for Data Cleaning
- Data Validation Techniques
Data Visualization using Power BI
- Introduction to Power BI
- Power BI Desktop Interface
- Data Importing and Transformation
- Data Modeling
- Creating Dashboards
- DAX Basics
- Visualization Techniques
- Publishing and Sharing Reports
- Power BI Service
- Data Refresh and Scheduling
- Integrating Power BI with Other Tools
- Security Features in Power BI
- Advanced DAX Functions
Machine Learning
- Introduction to Machine Learning
- Types of Machine Learning (Supervised, Unsupervised, Reinforcement)
- Data Preprocessing
- Feature Engineering
- Regression Analysis
- Classification Techniques
- Decision Trees
- Random Forests
- Support Vector Machines
- Neural Networks
- Deep Learning
- Clustering Algorithms
- Dimensionality Reduction
- Ensemble Methods
- Model Evaluation and Validation
- Hyperparameter Tuning
- Machine Learning Pipelines
