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.
Business Statistics
Descriptive Statistics
- Data Types
- Measure of Central Tendency
- Measures of Dispersion
- Graphical Techniques
- Skewness & Kurtosis
- Box Plot
Probability
- Random Variable
- Probability Distribution
- Normal Distribution
- SND (Standard Normal Distribution)
- Expected Value
Inferential Statistics
- Sampling Funnel
- Sampling Variation
- Central Limit Theorem
- Confidence Interval
- Hypothesis Testing
- 2 Proportion Test
- 2 Sample t-Test
- ANOVA and Chi-Square
Basics of Excel
- Introduction to Excel
- Navigating the Excel Interface
- Basic Excel Functions and Formulas
- Data Entry Techniques
- Formatting Cells and Sheets
- Data Sorting and Filtering
- Introduction to PivotTables
- Conditional Formatting for Data Insights
- Excel Functions for Statistical Analysis
- Date and Time Functions
- Lookup Functions (VLOOKUP, HLOOKUP)
Fundamentals of AI
- Introduction to Artificial Intelligence
- History of AI
- AI Applications and Case Studies
- Ethics in AI
- Basic Machine Learning Concepts
- Supervised vs. Unsupervised Learning
- Neural Networks
- Deep Learning Fundamentals
- Natural Language Processing (NLP)
- Computer Vision Basics
- Robotics and AI
- AI in Business and Industry
- Future Trends in AI
Analytics in Python
- Introduction to Python
- Python Setup and Environment Configuration
- Basic Syntax and Variables
- Data Types in Python
- Control Structures (if-else, loops)
- Functions and Modules
- Exception Handling
- NumPy for Numerical Data
- Pandas for Data Manipulation
- Data Cleaning Techniques
- Introduction to Statistics with Python
- Basics of Data Gathering and Web Scraping
