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Ashoka - Top B.Tech/Engineering College in Hyderabad, IndiaAshoka - Top B.Tech/Engineering College in Hyderabad, India
  • Home
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      • Founder & Chairman’s Message
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      • Computer Science & Engineering
      • Structural Engineering
    • Under Graduate
      • Computer Science Engineering
      • Computer Science & Engineering (AI & ML)
      • Electronics & Communication Engineering (Data Science*)
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      • Civil Engineering
      • Electrical & Electronics Engineering
    • Diploma
      • Diploma in Mechanical Engineering
      • Diploma in Civil Engineering
      • Diploma in Electrical & Electronics Enggineering
    • Certification Courses
    • Summarized Course Duration
  • Admissions
    • Programmes Offered
    • Eligibility
    • Scholarship Schemes & Prizes
    • Education Loan
    • Fee Structure
    • Transportation Fee
    • Payment Procedure
    • Important Dates
    • Prospectus
    • Application Form
  • Life@ASHOKA
    • ASHOKA Orientation Programme
    • Alumni Association
    • Hostel & Dining
    • Sports
    • Campus Amenities
      • Wifi-campus/E-Classroom
      • Open Air Theatre
      • Transport
      • A Hub
      • World Class Cafeteria
      • Smart Classroom
      • Internet Cafe/Computing Centre
      • NPTEL Classroom
      • Health Services
    • Student Clubs & Chapters
    • Magazine
  • Why Ashoka
    • Incubation Centre
    • NPTEL Local Chapter
    • Uptrend Technology
      • Flipped Learning/Classroom
      • Blended Learning
      • Think, Pair & Share
      • Classroom 4.0
    • Collaborations (MoUs)
    • Centre Of Excellence
    • Conferences
    • FDPs/Workshops/Seminars
    • Library
    • National Service Schemes (NSS)
    • Discipline & Grievance
      • General Rules
      • Anti-Ragging Cell
      • Women’s Cell
      • Hostel Rules
      • Visitor’s Rules
    • Green Campus
  • Placements
    • Placement Team
    • Placement@Ashoka
    • Recruited Students
    • Placement Patrons
    • Internship Diaries
    • Our StartUps
    • Training & Placement Policies
    • Skill Development Cell
  • Downloads
    • Academic Calendar
    • Library Form
    • Syllabus
      • B.Tech and M.Tech
      • Diploma
    • Transport Form
    • Leave Form
    • No Dues Form
      • Faculty
      • Student
      • Hall-Ticket
    • Bonafide Certificate
  • Artificial Intelligence
  • Python Programming
  • Machine Learning
  • Deep Learning
  • Robotics
  • Matlab

Certification Course on Artificial Intelligence

About the Course

Artificial Intelligence (AI) is no longer science fiction. It is rapidly permeating all industries and having a profound impact on virtually every aspect of our existence. Whether you are an executive, a leader, an industry professional, a researcher, or a student - understanding AI, its impact and transformative potential for your organization and our society is of paramount importance. This specialization is designed for those with little or no background in AI, whether you have technology background or not, and does not require any programming skills. It is designed to give you a firm understanding of what is AI, its applications and use cases across various industries. You will become acquainted with terms like Machine Learning, Deep Learning and Neural Networks.

Furthermore, it will familiarize you with IBM Watson AI services that enable any business to quickly and easily employ pre-built AI smarts to their products and solutions. You will also learn about creating intelligent virtual assistants and how they can be leveraged in different scenarios. By the end of this specialization, learners will have had hands-on interactions with several AI environments and applications, and have built and deployed an AI enabled chatbot on a website – without any coding.

Course Objective:

  • To understand what is AI, its Applications and use cases and how it is transforming our lives
  • To describe several issues and ethical concerns surrounding AI
  • To explain terms like machine learning, deep learning and neural networks.
  • To provide a foundation in use of this AI for real time applications.

Course Outcome:

Upon successful completion of this course, students will be able to

  1. Expand knowledge about basic concepts of AI
  2. work with IBM Watson
  3. Create Chatbots without the need of writing any code

Course Duration:

3 Months

Course Content

S.NoContent
1What is AI? Applications and Examples of AI
2AI Concepts, Terminology, and Application Areas
3AI: Issues, Concerns and Ethical Considerations
4The Future with AI, and AI in Action
5Getting Started with AI using IBM Watson
6Watson AI Overview
7Watson AI Services
8More Watson AI Services
9Watson in Action
10Building AI Powered Chatbots without programming - Introduction
11Intents
12Entities
13Dialog
14Deployment
15Context Variables & Slots
16Digressions
17Final Exam
18Online Certification

Certification Course on Python Programming

About the Course

Python programming certification course enables students to learn data science concepts. This Python Course will also help students to gain knowledge in Python programming concepts such as data operations, file operations, object-oriented programming and various Python libraries such as Pandas, which are essential for Data Science.

 

Python Scripting is one of the easy languages to learn and is widely used from individuals to big organizations such as Google. This Python training starts with basic syntax of Python and continues to small GUI programs. Students will learn Python data types such as Tuples and Dictionaries, Looping, Functions and I/O handling. Python training will also give students an overview of Object Oriented Programming and Graphical application development. This course will explain some basics modules and their usage. At the end of the Python Scripting Training, individuals will have the skills to grow in Web-Development, GUI Application Programming, Game Development and writing powerful script for System Administration.

 

The Advanced Python Programming training course will give students a detailed overview of advance python programming topics like Leveraging OS services, Code graphical interfaces for applications, Create modules, Create and run unit tests, Define classes, Interact with network services, Query databases, Process XML data. This is an extensive hands-on training involving labs and exercises to students a practical and real-time exposure.

Course Objective:

  • Expose students to application development and prototyping using Python
  • To understand data Visualization and use of machine Learning in python.
  • To enable the student to gain automation skills using python programming language to manage network devices.
  • To prepare the students to use Python Programming in handling real world problems.

Course Outcome:

Upon successful completion of this course, students will be able to

 

  1. Students will be able to determine the methods to create and manipulate Python programs by utilizing the data structures like lists, dictionaries, tuples and sets.
  2. Students will be able to apply the best features of mathematics, engineering and natural sciences to program real life problems.
  3. Students will be able to design real life situational problems and think creatively about solutions of them.

Course Duration:

3 Months

Course Content

 

S.NoCourse Content
1Python language basic constructs
2Oops concepts in python
3Introduction to Programming Using Python
4Packages and functions in python
5Introduction to databases in python
6Importing data in python
7Python Lists
8Python Libraries(pandas)
9Exception handling in python
10Advanced python Programming
11Introduction to MongoDB in Python
12Python Programming for Network Engineering
13Introduction to data visualization in python
14Python for web Application
15Introduction to Machine Learning with python

Certification Course on Machine Learning

About the Course

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI. This course provides a broad introduction to machine learning, data mining, and statistical pattern recognition.

Topics include:

(i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks).

(ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning).

(iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.

Course Objective:

  • To introduce students to the basic concepts and techniques of Machine Learning.
  • To develop skills of using recent machine learning software for solving practical problems.
  • To gain experience of doing independent study and research.

Course Outcome:

Upon successful completion of this course, students will be able to

  1. Gain knowledge about basic concepts of Machine Learning
  2. Identify machine learning techniques suitable for a given problem
  3. Solve the problems using various machine learning techniques
  4. Design application using machine learning techniques.

Course Duration:

3 Months

Course Content

S.NoCourse Content
1Introduction
2Linear Regression with One Variable
3Linear algebra Review
4Linear Regression with Multiple Variables
5Running the program in Octave / MATLAB
6Logistic Regression
7Regularization
8Neural Networks
9Advice for Applying Machine Learning
10Machine Learning System Design
11Support Vector machines
12Unsupervised Learning
13Dimensionality Reduction
14Anomaly Detection
15Recommender systems
16Large Scale Machine Learning
17Application Example: Photo OCR
18Practice Exercises
19Online Certification

Certification Course on Deep Learning

About the Course

Deep Learning course builds a solid foundation by covering the most popular and widely used Deep Learning technologies and its applications including Computer vision, Artificial neural networks, convolutional neural networks for the students who are interested in machine learning, Artificial Intelligence and who also have knowledge in Python programming. Deep learning is a key technology behind driverless cars, enabling them to recognize a stop sign, or to distinguish a pedestrian from a lamppost. It is the key to voice control in consumer devices like Mobiles, tablets, TVs, and hands-free speakers.

Deep learning differs from traditional machine learning techniques (like classification, clustering etc.) in a way that they can automatically learn representations from data such as images, video or text, without introducing hand-coded rules or human domain knowledge. Deep learning changes how you think about representing the problem that you’re solving with analytics. It moves from telling the computer how to solve a problem to training the computer to solve the problem itself.

Course Objective:

  • To understand the concept of artificial neural networks, convolutional neural networks, and recurrent neural networks.
  • To learn the foundations of Deep Learning, including how to build neural networks and machine learning projects.
  • To learn deep learning methodologies to process not only image based datasets but also raw text, numbers etc.

Course Outcome:

Upon successful completion of this course, students will be able to

  1. Identify the deep learning algorithms which are more appropriate for various types of learning tasks in various domains.
  2. Develop ability to independently solve business problems using deep learning techniques.
  3. Apply such deep learning mechanisms to various learning and real world problems.

Course Duration:

3 Months

Course Content

S.NoCourse Content
1Introduction to Deep learning
2Neural Networks Basics
3Shallow neural networks
4Deep Neural Networks
5Practical aspects of Deep Learning Optimization algorithms
6Hyperparameter tuning
7Batch Normalization and Programming Frameworks
8Machine Learning Strategies
9Foundations of Convolutional Neural Networks
10Deep Convolutional models: case studies Object detection
11Special applications: Face recognition & Neural style transfer
12Recurrent Neural Networks
13Natural Language Processing & Word Embeddings
14Sequence models & Attention mechanism

Certification Course on Design of Robot using Embedded Systems

About the Course

This course is introduced to meet the growing demand for trained engineers in the field of Robotics. It provides sound, proportional knowledge in hardware as well as software development in their applications. Robotic is a course that involves design, development and operation of robots and it is an overlap of several engineering disciplines like electrical, mechanical, electronics, computer science and artificial intelligence. The students come from diverse backgrounds, but united by our common passion for robotics that will lead the future science and technology. The course contains Embedded C and Atmel Studio 6.0, I/O interfacing on AVR based microcontrollers and debugging, timers and delay generation, DC motor control and PWM generation for velocity control and Analog-to-Digital conversion and white line follower.

Course Objective:

  • To train the students through hands-on projects are imperative in producing successful innovators in the field of Robotics.
  • To provide the competitive advantage to colleges in attracting talented students.
  • To facilitate the infrastructure creation by sharing its experience and expertise.
  • To encourage to use robots to solve real life problems.

Course Outcome:

Upon successful completion of this course, students will be able to

  1. Create embedded systems, robotics technology and mechatronics based products.
  2. Provides platform to design, develop, program and test robots for various applications.
  3. Students can participate in national and international robotics competitions.
  4. Improve engineering projects with help of e-yantra open source community.
  5. Exposure to job opportunities in robotics.

Course Duration:

3 Months

Course Content

S.NoCourse Content
1Introduction
2Atmel Studio 6 IDE
3Writing and debugging C code snippets
4Programming and charging procedure for Firebird V
5Function of I/O ports and the associated registers
6Interface I/O peripherals like switch and Bar graph LEDs
7Different LCD commands and ASCII encoding using Firebird V
8Displaying text at different positions on the LCD and implementing a simple scrolling display
9TIMERs and their registers in ATmega2560 for configuring TIMERs in Firebird
10Manipulating TIMERs to generate delays as required without using "_delay_ms()" function.
11Direction control of DC motors present on Firebird V
12PWM or velocity control of the motors present on Firebird V
13sharp sensors and white line sensors
14ADC (analog to digital conversion) on Firebird
15White lines following through writing a code to make Firebird V follow a white line

Certification Course on MATLAB Programming

About the Course

This course teaches computer programming to those with little to no previous experience. It uses the programming system and language called MATLAB to do so because it is easy to learn, versatile and very useful for engineers and other professionals. MATLAB is a special-purpose language that is an excellent choice for writing moderate-size programs that solve problems involving the manipulation of numbers. The design of the language makes it possible to write a powerful program in a few lines. The problems may be relatively complex, while the MATLAB programs that solve them are relatively simple: relative that is, to the equivalent program written in a general-purpose language, such as C++ or Java. As a result, MATLAB is being used in a wide variety of domains from the natural sciences, through all disciplines of engineering, to finance, and beyond, and it is heavily used in industry. Hence, a solid background in MATLAB is an indispensable skill in today’s job market.

Nevertheless, this course is not a MATLAB tutorial. It is an introductory programming course that uses MATLAB to illustrate general concepts in computer science and programming. Students who successfully complete this course will become familiar with general concepts in computer science, gain an understanding of the general concepts of programming, and obtain a solid foundation in the use of MATLAB. Students taking the course will get a MATLAB Online license free of charge for the duration of the course. The students are encouraged to consult the eBook that this course is based on. More information about these resources can be found on the Resources menu on the right.

Course Objective:

  • To familiarize the student in introducing and exploring MATLAB.
  • To enable the student on how to approach for solving Engineering problems using programming.
  • To prepare the students to use MATLAB in their project works.
  • To provide a foundation in use of this software’s for real time applications.

Course Outcome:

Upon successful completion of this course, students will be able to

  1. Express programming for engineering problems.
  2. Write basic mathematical, electrical, electronic problems in MATLAB.
  3. Do projects in image processing, control system using MATLAB.

Course Duration:

3 Months

Course Content

S.NoCourse Content
1Introduction
2Commands
3MATLAB Editor & Running Scripts
4Vectors and Matrices
5Indexing into and Modifying Arrays
6Array Calculations
7Calling Functions
8Obtaining Help
9Plotting Data
10Review Problems
11Importing Data
12Logical Arrays
13Programming
14Project I & II
15Online Certification

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