Course overview
Build your career in Autonomous software engineering
Autonomous Vehicles (AV) reduced road-crash risk, traffic congestions, enhanced safety and security, secured mobility for disabled individuals and non-drivers, and increased comfort and flexibility. AV technology has driven the major automakers to work with Tier 1 suppliers & startups to develop the matured technology for AV’s. The Global Autonomous Vehicle Market was valued at USD 54.21 billion in 2019 and is estimated to garner USD 2,044.93 billion by 2030, at a CAGR of 39.1% during the forecast period, from 2020 to 2030. Aggressive interest & growth in AV sector would require well trained engineers to develop computing & control hardware & software algorithms, vehicle integration, calibration, testing, validation, safety & more such areas.
This master course you will learn & master the software algorithms that power the AV. We will use tools & concepts such as ROS, Rviz, Gazebo, Open CV, Tensor flow, Keras, Control systems, image processing, sensor fusion, Machine Learning & Artificial Intelligence, Embedded hardware & software. We will also build an AV using real time hardware to implement the AV algorithms to gain real world experience.
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The autonomous vehicle algorithm engineering course is available to learn online. The course duration is 9 months and is limited to 5 participants intake.
Duration & Slots -
Applications are now accepted for freshers or experienced up to 2 years, should be from the background of studies (BE/BTech/MTech) in Mechanical/Automotive/Electronics & Electrical are accepted. (Program is also applicable for students who are planning to take up master's abroad in Automotive/Autonomous engineering)
Who can apply -
Participants can expect to get placed at OEM / Tier 1 / Tier 2 and at Engineering service companies. *** Average salary of placed students varied from 3 lakh to 6 lakh per annum.
Placements
Key highlights of the course
Build projects to gain similar industry experience
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The course is taught practically with the help of tools & software’s used in industry
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The course consists of 12+ minor projects & 3 majors projects
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The course will cover the complete life cycle of from software development, hardware configuration to calibration, testing & validation
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The course has the extensive depth of curriculum to meet any job profile for 0 to 2 years of experience bandwidth
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Course graduates will be supported to start a career in core sector (100% placement)
Course curriculum
- Programming tool, workbenches & OS foundation
- Python
- Robotic Operating System (ROS)
- Ubuntu
- Expertise ROS
- ROS framework
- ROS topics and Nodes
- Robot links and joints
- Forward and Inverse Kinematics
- Publisher and Subscriber programming
- Foundation to Rviz & Gazebo
- Forward and Inverse Kinematics programming of UR5
- Forward and Inverse Kinematics programming of Delta robot
- Localisation
- Types of sensors
- Odometry sensor and its parameters
- Joint Distribution & Conditional Probability
- Baye's filter 1D localisation
- 2D Baye's filter localisation
- Particle filter localisation
- Mapping
- Laser sensor and its parameters
- Occupancy grid mapping
- Bresenham's line algorithm
- Control system engineering foundation
- Practical design of PID controllers
- Foundation to MPC
- PID controller for tank water level control
- PID controller for furnace temperature
- RLC circuit tuning with PID controls
- Pitch angle control system for drone
- Motion Planning
- Path Planning
- Grid based representation of environment
- Dijkstra’s algorithm
- A-star algorithm
- RRT and RRT* algorithm
- PID based motion control
- Programming Dijkstra’s algorithm for a maze
- Programming A-star algorithm for a maze
- Programming RRT and RRT* algorithm in a given environment
- Programming and tuning PID controller for mobile robot
- Foundation to Machine learning
- Linear Regression and Curve Fitting
- Logistic Regression
- Decision trees
- Random Forest
- K-Nearest algorithm
- K Means
- Reinforcement Learning
- Q Learning
- Predictive Maintenance
- Data Wrangling
- Confusion Matrix, F1-Score, ROC & ROS-AUC curve
- Programming Linear Regression for salary prediction
- Programming Logistic regression for job prediction
- Movie decision making based on decision tree
- Number recognition based on random forest
- Flower species classification based on K-Nearest Neighbour
- Flower cluster classification based on K means
- Programming reinforcement learning for material transportation
- Machine Learning based Predictive Maintenance of Aircraft Engine
- Computer vision
- Foundation to Open CV
- Lane Detection
- Canny Edge Detection
- Hough Transformation on an image
- Image Distortion
- Programming Lane detection algorithm
- Programming Canny edge detection algorithm
- Neural networks
- Foundation to TensorFlow & Keras
- Back and forward propagation
- Convolutional neural networks
- Convolution of an image
- Pooling
- rectified linear activation function
- Programming a neural network algorithm
- Programming CNN algorithm
- Building the algorithm for Self-Driving car
- Convolution of an image
- Pooling
- Rectified linear activation function
- Behavior planning
- Programming a mobile robot with three cameras
- Programming image and vehicle data collection algorithm
- Programming CNN for self-driving car steering decision
- Programming a motion control algorithm for self-driving car
- Programming behavior planning for self-driving car
- Embedded programming & hardware for autonomous vehicle
- Embedded C
- Fundamentals of circuit components
- Fundamentals of circuit design
- Micro controllers hands-on (STM/TI/NXP)
- Micro processor (Raspberry pi/Nvidia)
- Sensor data acquisition
- Camera
- LIDAR
- Sensor data processing
- Build an autonomous vehicle
- Build a AV with RGBD camera, Lidar with Nvidia JETSON computation board
- Configure power management, motors & controls
- Configure data communication between AV & computer
- Perform sensor data acquisition & filtering
- Implement localisation, mapping & motion control
- Implement computer vision
- Implement Neural networks to teach the AV
- Teach & test the AV for different track profiles
- Decision making with sensor data
- Throttle, brake & steering control of AV with ML & AI
- Teach AV at complex environments
- Industry practices
- ASPICE
- Functional safety (ISO 26262)
- Communication protocols
Master course projects
Define your experience through
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Learn ROS, Forward and Inverse Kinematics with UR5 and delta robot programming
ROS & Robotics -
Baye's filter 1D localization, 2D Baye's filter localization & Particle filter localization
Robot Localization -
Occupancy grid mapping
Robot Mapping -
Design & tune PID for projects, 1) Controller for tank water level control, 2) controller for furnace temperature, 3) RLC circuit tuning and 4)Pitch angle control system for drone
Control System -
Maze solving with Dijkstra’s & A-star algorithms, Programming RRT and RRT* algorithms, Programming and tuning PID controller for mobile robot
Robot Motion Control -
Lane Detection & Canny Edge Detection
Computer vision -
Programming a neural network algorithm & CNN algorithm
Neural Network -
Programming CNN for self-driving car steering decision & Programming behavior planning for self-driving car
Self-Driving Car
Master course Includes
Course fee & payment option
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Autonomous Vehicle Algorithm Engineer
10 x ₹17,700.00
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