Computer Science & Engineering (Data Science)

About Department

INTRODUCTION

As technology continues to evolve at an unprecedented pace, the demand for professionals skilled in data science has skyrocketed. One field that has witnessed a significant transformation is Computer Science and Engineering (CSE) departments in engineering colleges. With the emergence of data-driven decision making and the increasing importance of big data analytics, CSE departments have incorporated data science as a crucial component of their curriculum.

THE GROWING IMPORTANCE OF DATA SCIENCE

Data science has emerged as a critical discipline in today’s digital age. It involves extracting actionable insights from vast amounts of structured and unstructured data, enabling organizations to make informed decisions and gain a competitive edge. Industries such as finance, healthcare, marketing, and e-commerce heavily rely on data science to optimize their operations, improve customer experiences, and drive innovation.

ABOUT ACE ENGINEERING COLLEGE CSE (DATA SCIENCE) DEPARTMENT

With the rapid evolution of technology and the increasing amount of available data, the demand for professionals skilled in data science has grown exponentially. Our CSE (Data Science) department aims to meet this demand by providing a comprehensive curriculum that prepares students with the essential skills and knowledge needed for success in this field.

At the core of our department’s vision is the belief that data is at the heart of innovation and informed decision-making. Our faculty members, who are renowned experts in their respective fields, are committed to imparting the latest methodologies and industry best practices to our students. They continuously engage in research, ensuring that our curriculum remains up-to-date and aligned with current industry requirements.

The department is home to a group of highly skilled and experienced faculty members with knowledge in a variety of subjects. Two of the faculty members have doctorates, and one is currently obtaining a Ph.D. In addition, three faculty members are enrolled in the University of Hyderabad’s Artificial Intelligence and Machine Learning Diploma program.

Duration: 4 years (Regular) / 3 years (Lateral Entrance)

No. of Semesters: 8 (Regular) / 6 (Lateral Entrance)

No. of Seats: Total – 180 (Status of NRI Approval – Yes)

Eligibility: Education is based on the 10+2 system. Student must have passed the subjects of Physics, Chemistry, and Mathematics in the qualifying examination

Scope for Higher Studies: M.E. / M.Tech / M.B.A./ M.S.

The CSE department specializing in Data Science has impressive facilities and a fully equipped computer lab that is tailored to the unique requirements of our data science students. We offer an abundant range of resources, such as advanced computing clusters and access to various datasets, allowing students to gain practical experience and enhance their problem-solving abilities.

The department encourages students to actively participate in research projects and engage in internships with leading organizations. These opportunities provide invaluable experiences and allow students to apply the knowledge they acquire in real-world settings. Additionally, we facilitate workshops, seminars, and guest lectures by industry professionals to bridge the gap between academia and industry, allowing students to expand their network and stay abreast of the latest trends and developments.

Collaboration is a key aspect of our department’s ethos, and we actively foster interdisciplinary partnerships within the institution and with external organizations. This collaborative approach serves to enhance the scope of research and enrich the learning environment, enabling students to tackle complex, real-world problems that require cross-domain expertise.

Graduates from our CSE (Data Science) department are well-positioned for exciting career opportunities in various sectors, including technology, finance, healthcare, and more. Armed with a deep understanding of data analytics, statistical modelling, and machine learning algorithms, our graduates are sought after by industry leaders for their analytical and problem-solving skills.

Finally, our engineering college’s CSE (Data Science) department is an ideal place for ambitious data scientists. Our education program encompasses both theoretical learning and hands-on experience, enabling students to develop expertise in the field of data science. Through top-notch faculty, state-of-the-art facilities, and a collaborative mindset, we empower our students with the necessary resources to make innovative advancements in the continuously evolving realm of data science.

OBJECTIVES:

To equip the students with strong fundamental concepts, analytical capability, programming and problem solving skills.
To create an academic environment conducive for higher learning through student training, self learning, sound academic practices and research
endeavors.
To make the students industry ready and to enhance their employability through training and internships. To make students job-ready by applying what you learn and building real-life projects
To improve department industry collaboration through interaction including participation in professional society activities, guest lecturers and industrial visit.
To provide opportunities in order to promote organizational and leadership skills in students through various co-curricular and extra – curricular activities

Vision and Mission

Vision of the Department

Our objective is to cultivate an unparalleled educational journey that empowers individuals to thrive in their chosen professions. We achieve this by immersing students in a dynamic, interactive learning environment while also offering ample opportunities for research and exploration of real-world applications. Our program strives to produce data science professionals who possess exceptional expertise, enabling them to be catalysts of innovation within the industry.

Mission of the Department

Empowering the Future of Technology and Innovation

At the heart of the CSE Data Science Department’s mission is the goal to develop professionals with a strong understanding of mathematics. By emphasizing subjects such as probability and statistics, linear algebra, and calculus, students are equipped with the necessary tools to analyze and interpret complex data sets. These foundational skills serve as the building blocks for more advanced data science techniques, allowing students to tackle real-world problems with confidence and precision.
In addition to a solid mathematical foundation, the department is committed to providing students with an education that keeps pace with the rapidly evolving landscape of AI and data science. By staying abreast of the latest technologies and methodologies, students are exposed to the most cutting-edge tools and techniques in the field. This enables them to adapt to the ever-changing demands of the industry and ensures that they are equipped with the skills necessary to excel in their careers.
Quality education and value-based learning are core principles of the CSE Data Science Department. By imparting knowledge that goes beyond mere technical skills, the department aims to foster a sense of innovation and creativity among its students. By encouraging critical thinking and problem-solving abilities, students are empowered to push the boundaries of what is possible in the field of data science. This commitment to excellence not only benefits the individual students but also contributes to the overall satisfaction of all stakeholders involved.
The department also recognizes the importance of socially responsive research and innovation. By integrating ethical considerations into the curriculum, students are encouraged to use their skills for the betterment of society. This approach ensures that the impact of data science goes beyond commercial applications and extends into areas such as healthcare, social justice, and sustainability.
Moreover, the CSE Data Science Department prides itself on its unwavering commitment to harnessing the cutting-edge innovations in high-performance computing hardware and software. By continuously pushing boundaries and embracing technological breakthroughs, the department empowers researchers with the tools they need to analyze and process large datasets in fields such as data science

PEOs, WK, POs and PSOs

Program Educational Objectives (PEOs)

To introduce the fundamentals of science and engineering concepts essential for a data architect / data scientist.
To inculcate the knowledge of mathematical foundations and algorithmic principles for effective problem solving.
To provide knowledge in data science for modern computational data analysis and modeling methodologies.
To provide the knowledge in artificial intelligence techniquesand apply them to develop relevant models and real time products.
To impart knowledge to analyze, design, test and implement the model required for various applications.
To hone personality skills, trigger social commitment and inculcate societal responsibilities.

Knowledge and Attitude Profile (WK)

WK1: A systematic, theory-based understanding of the natural sciences applicable to the discipline and awareness of relevant social sciences.

WK2: Conceptually-based mathematics, numerical analysis, data analysis, statistics and formal aspects of computer and information science to support detailed analysis and modelling applicable to the discipline.

WK3: A systematic, theory-based formulation of engineering fundamentals required in the engineering discipline.

WK4: Engineering specialist knowledge that provides theoretical frameworks and bodies of knowledge for the accepted practice areas in the engineering discipline; much is at the forefront of the discipline.

WK5: Knowledge, including efficient resource use, environmental impacts, whole-life cost, reuse of resources, net zero carbon, and similar concepts, that supports engineering design and operations in a practice area. WK6: Knowledge of engineering practice (technology) in the practice areas in the engineering discipline.

WK7: Knowledge of the role of engineering in society and identified issues in engineering practice in the discipline, such as the professional responsibility of an engineer to public safety and sustainable development.

WK8: Engagement with selected knowledge in the current research literature of the discipline, awareness of the power of critical thinking and creative approaches to evaluate emerging issues.

WK9: Ethics, inclusive behavior and conduct. Knowledge of professional ethics, responsibilities, and norms of engineering practice. Awareness of the need for diversity by reason of ethnicity, gender, age, physical ability etc. with mutual understanding and respect, and of inclusive attitudes.

Program Outcomes (POs)

PO1: Engineering Knowledge: Apply knowledge of mathematics, natural science, computing, engineering fundamentals and an engineering specialization as specified in WK1 to WK4 respectively to develop to the solution of complex engineering problems.

PO2: Problem Analysis: Identify, formulate, review research literature and analyze complex engineering problems reaching substantiated conclusions with consideration for sustainable development. (WK1 to WK4)

PO3: Design/Development of Solutions: Design creative solutions for complex engineering problems and design/develop systems/components/processes to meet identified needs with consideration for the public health and safety, whole-life cost, net zero carbon, culture, society and environment as required. (WK5)

PO4: Conduct Investigations of Complex Problems: Conduct investigations of complex engineering problems using research-based knowledge including design of experiments, modelling, analysis & interpretation of data to provide valid conclusions. (WK8)

PO5: Engineering Tool Usage: Create, select and apply appropriate techniques, resources and modern engineering & IT tools, including prediction and modelling recognizing their limitations to solve complex engineering problems. (WK2 and WK6)

PO6: The Engineer and The World: Analyze and evaluate societal and environmental aspects while solving complex engineering problems for its impact on sustainability with reference to economy, health, safety, legal framework, culture and environment. (WK1, WK5, and WK7)

PO7: Ethics: Apply ethical principles and commit to professional ethics, human values, diversity and inclusion; adhere to national & international laws. (WK9)

PO8: Individual and Collaborative Team work: Function effectively as an individual, and as a member or leader in diverse/multi-disciplinary teams.

PO9: Communication: Communicate effectively and inclusively within the engineering community and society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations considering cultural, language, and learning differences

PO10: Project Management and Finance: Apply knowledge and understanding of engineering management principles and economic decision-making and apply these to one’s own work, as a member and leader in a team, and to manage projects and in multidisciplinary environments.

PO11: Life-Long Learning: Recognize the need for, and have the preparation and ability for i) independent and life-long learning ii) adaptability to new and emerging technologies and iii) critical thinking in the broadest context of technological change. (WK8)

Program Specific Outcomes (PSOs):

PSO1: Understand, analyze and develop essential proficiency in the areas related to data science in terms of underlying statistical and computational principles and apply the knowledge to solve practical problems.

PSO2: Implement data science techniques such as search algorithms, neural networks, machine learning and data analytics for solving a problem and designing novel algorithms for successful career and entrepreneurship.

About the Course

ABOUT THE COURSE

About the Course

This comprehensive course offers numerous advantages for understanding key concepts in data science. It provides a deep dive into the analysis of big data, effectively handling large datasets, and optimizing operations to efficiently manage vast amounts of information. By enrolling in this all-in-one data science course, you will gain valuable knowledge about various tools, IDEs, frameworks, and techniques that are instrumental in mastering different areas within data science. The curriculum begins by introducing the fundamental building blocks of data science, such as foundational principles, core concepts, and basic programming elements. Subsequently, it progresses to cover essential aspects like data visualization and analytics using popular platforms like Excel, SQL, and Tableau. These modules delve into crucial skills, including data extraction strategies, advanced manipulation techniques, detailed analysis methodologies, relevant reporting practices, and constructing intuitive business dashboards.

Top Programming languages for Data Science:

Python
R Programming
Java script
Java
SQL
Scala
Key Areas of Data Science

IDE:

Pycharm
Jupyter

Data Analysis:

FE
Data Wrangling
EDA (explore data analysis)

Data Visualization:

Tableau
Power BI
MATplotlib
Ggplot
Seaborn

WEB Scraping:

Beautiful Soup
Scrapy
URL LIB

Key areas of data science

Data Engineering and Data Warehousing
Data Engineering involves converting data into a format that is suitable for analysis. This often includes overseeing the origin, organization, integrity, storage, and availability of the data in order to enable its query and analysis by other analysts..
related jobs: Data Engineer, Database Developer, Data Analyst
Data Mining and Statistical Analysis
Data Mining involves the utilization of statistical techniques such as exploratory data analysis and predictive modeling to identify patterns and trends in data obtained from various sources. This individual has the ability to analyze a business problem, transform it into a specific question about data, develop predictive models to address this question, and effectively communicate their findings through storytelling.
related jobs: Data Scientist, Business Analyst, Statistician
Cloud and Distributed Computing
Designing and implementing the necessary infrastructure and platforms for cloud computing and distributed systems is what Cloud and System Architecture entail. This role also involves analyzing system requirements, ensuring secure integration with existing applications, and aligning them with business needs.
related jobs: Cloud Architect, Cloud Engineer , Platform Engineer
Database Management and Architecture
The primary responsibility of this role is to create, implement, and manage databases that handle large volumes of complex data transactions for specific services or groups.
related jobs: Database Analyst, Database Administrator, Data Specialist
Business Intelligence and Strategy
BI encompasses various essential tasks, such as enhancing data sources for greater precision and ease, creating customized analytics solutions, overseeing dashboards and reports for stakeholders’ benefit, identifying opportunities to optimize reporting and analysis practices – including aspects like data integrity, test design, validation, and documentation.
related jobs: BI Engineer, BI Developer, BI Analyst, Data Strategist
ML / Cognitive Computing Development
Most individuals associate data science with “creating robots”. This field encompasses a more advanced and intricate version of data mining and statistical analysis. The primary focus lies in acquiring the necessary input to fuel the model, which involves tasks such as constructing data pipelines, identifying convenient sources for data, conducting A/B testing, and establishing benchmarking infrastructure. Once these preliminary steps are completed, attention may shift towards building the actual algorithms or models. However, this phase often relies on well-established industry tools and statistical techniques. It is worth noting that this particular area has become a popular buzzword in numerous organizations; therefore it is advisable to explore specific sub-fields within it to gain a clear understanding of one’s preferences.
related jobs: ML Engineer, AI Specialist, Cognitive Developer, Researcher
Data Visualization and Presentation
Presenting data in a visually pleasing manner has become an integral aspect of various roles, such as business analyst and data scientist. When these areas are designated as official positions within a company, the primary responsibility is to develop tailored BI solutions for teams and customers based on specific business needs and use cases. In some instances, this may involve more emphasis on graphic design skills..
related jobs: Data Viz Engineer, Data Viz Developer, Software Developer
Operations-Related Data Analytics
If you do not identify as highly technical but still have a knack for problem-solving and optimizing processes, these could be suitable career options. These positions involve utilizing the tools and data provided by the rest of the data science team to identify areas for improvement in various aspects of business operations, such as logistics, technology, finance, or human resources.
related jobs: Planning Analyst, Decisions Analyst, Communications Analyst, etc
Market-Related Data Analytics
The level of technical expertise required for these roles varies depending on the analysis level and company. Typically, individuals in these positions concentrate more on external data pertaining to customers, sales, and marketing. However, their overall objective is similar to that of operations personnel: monitoring performance and identifying potential opportunities.
related jobs: Web Analyst, Product Analyst, Market Analyst, Sales Analyst
Sector-Specific Data Analytics (Healthcare, Finance, Insurance, etc.)
Finally, individuals with a background in sectors like Healthcare or Finance and a need for specialized knowledge to assess data may consider exploring entry-level analyst roles within companies operating in these industries. It is important to note that the specific technical skills required for such positions will vary depending on the hiring organization’s expectations and preferred tools.
related jobs: Data Analyst, Business Analyst, Data Scientist — specialized

Opportunities

Data science is gaining immense popularity and becoming a lucrative career choice due to its high salaries and abundant opportunities. This field, widely regarded as one of the most sought-after careers of the 21st century, is witnessing an exponential growth in job openings worldwide.

India, like many other countries, is also witnessing a data explosion and experiencing increased demand for data scientists as more companies embrace this technology-driven discipline.

Data Scientist
Data Analyst
Data Engineer
Business Intelligence Developer.
Data architect
Statistician
Business Analyst
Machine Learning engineer
Database Administrator

Uniqueness of Data Science

UNIQUENESS OF DATA SCIENCE

The demand for data scientists is rapidly increasing each day due to their extensive knowledge and expertise in various fields such as machine learning, statistics, mathematics, computing science, data visualization, and communication. As companies grapple with large amounts of data, they rely on these professionals to extract valuable insights that can enhance their business strategies while adapting to evolving technologies in the market. Consequently, there’s a growing need for skilled individuals who possess reliable data science skills. These experts proficiently manipulate vast datasets using advanced statistical techniques and visualization methods to predict potential outcomes and identify possible risks. Additionally, this escalating demand also offers promising career opportunities for both students and established professionals alike.

In a typical day, the tasks of a data scientist involve extracting information from various sources through the use of APIs or constructing ETL pipelines. Data cleansing is performed using programming languages such as R or Python. They search for more efficient methods to analyze data by exploring disparate and disconnected sources. Data scientists possess knowledge in specific areas and have expertise in managing and interpreting data to solve complex problems. Additionally, they construct models and algorithms that allow them to uncover patterns and trends within extensive datasets. Finally, these insights are communicated visually to stakeholders using visualization tools.

Currently, the role of a ‘data scientist’ is regarded as one of the most attractive jobs in the 21st century. While it is essential to have experience with R, Python, Cloud computing, machine learning, multivariable calculus, probability and statistics, SQL,Tensorflow,and big data analysis skills alongside soft skills like data storytelling,data communication,business acumen and critical thinking for success in this highly competitive field; there are certain additional skills that can set individuals apart. Some examples include:

Data Wrangling: Working with messy and disorganized data sets can be challenging. The database fields may lack clear definitions, contain irrelevant values, or have inconsistent uses within the same field. Additionally, outliers in the data may not have a clear explanation. Therefore, it is essential to transform, standardize, normalize and clean the data before conducting any modeling work in order to extract meaningful insights from it. Data wrangling refers to the process of converting data from one format to another. This task requires patience as no amount of time or knowledge can compensate for a poorly structured dataset. For example, Python offers tools for effective Data Wrangling techniques.

Web Analytics: With the rise of social media platforms such as Facebook, Twitter, Instagram, and more, there is a wealth of untapped data available that can greatly benefit customer services and improve brand offerings. To gain valuable insights into target customers, it is essential to utilize web analytics algorithms to collect online data effectively. Popular web analytic tools like Kissmetrics, Mixpanel, and Google Analytics provide companies with the ability to track website traffic and analyze it for strategic purposes.

Visualization and Storytelling: Although data visualization is an important aspect of a data science role, recruiters may not place significant emphasis on this skill during the hiring process. However, by utilizing data visualization techniques, individuals can effectively illustrate the outcomes derived from machine learning algorithms. As previously mentioned, this enables data scientists to explain and communicate their discoveries to both technical and non-technical audiences. Several helpful tools for data visualization include Matplotlib, d3.js, Tableau, and ggplot. Additionally, incorporating visually appealing charts and graphs of high quality facilitates clear and concise presentation of findings. Moreover it is crucial for a data scientist to possess a imaginative mindset in order to enhance their ability to tell stories with the provided information through engaging stakeholders when necessary.

Career Enhancement Programme – held on 06-05-2023

The Kalam Institute of Youth Excellence is a transformative initiative aimed at realizing the vision and mission of Dr. A. P. J. Abdul Kalam. Recently, in collaboration with ACE Engineering College, KIYE organized a one-day Career Enhancement Programme on May 6th, 2023. A total of 1200 students from ten engineering colleges participated in this programme where they were provided insights into various aspects of career planning and entrepreneurship. The Chief Guest for the event was Dr.G Sateesh Reddy, Scientific Advisor to Raksha Mantri, who spoke about the importance of mind management and developing creative skills through simple techniques using real-life examples. Additionally, as a special guest speaker, Dr.S Somanth – Secretary Department of Space & Chairman ISRO shared valuable insights on how to enhance skills in advanced technologies and explore global opportunities.

Faculty

FACULTY

Name of the Programme	CSE (Data Science)
Approved Intake (2024)	180
No. of Faculty Members	35
	Cadre	Number
	Professor	03
	Assoc. Professor	07
	Asst. Professor	25

Faculty Profile	Qualification	No. of Faculty
	Ph.D	04
	Ph.D(Pursuing)	09
	Post Graduate	22
Technical Staff	Technical Staff	01
	Programmers	02

Name	Dr. P. Chiranjeevi
Designation	HoD & Professor
Qualification	B.Tech(CSE), M.Tech(CSE), Ph.D(CSE), Dip in AIML (UoH)
Professional Exp.	16 Years Teaching \| 6 Months Industry
Research Interests	Text Mining, Data Mining, Natural Language Processing, Opinion Mining, Sentiment Analysis
Registration Number	5569-150423-175518

Name	Dr. Ralla Suresh
Designation	Professor
Qualification	B.Tech, M.Tech, Ph.D
Professional Exp.	16 Years
Research Interests	Artificial Intelligence and Deep Learning
Registration Number	0862-150505-162448

Name	Mr. Md.Younus Shariff
Designation	Associate Professor
Qualification	B.Tech., M.Tech
Professional Exp.	15 Years Teaching \| 1 Year Industry
Research Interests	MERN Stack and Mobile Development
Registration Number	70150405-155529

Name	Mr. Daram Narasimha Rao
Designation	Associate Professor
Qualification	M.Tech (CSE)
Professional Exp.	28 Years
Research Interests	Operational Research
Registration Number	40150407-124112

Name	Mr. S. Rajendra Kumar
Designation	Associate Professor
Qualification	M.Tech,(Ph.D)
Professional Exp.	19 Years
Research Interests	RF IC Inductor
Registration Number	8363-161223-145310

Name	Mrs. A Sarala Devi
Designation	Associate Professor
Qualification	MCA., M.Tech(CSE) (Ph.D)
Professional Exp.	13 Years
Research Interests	Artificial Intelligence, Neural Networks
Registration Number	37150404-195953

Name	Mr. K Raghupathi
Designation	Assistant Professor
Qualification	M.Tech (CSE), (Ph D)
Professional Exp.	20 Years
Research Interests	Big Data
Registration Number	7025-221125-120015

Name	Mr. Gollapalli Parwateeswar
Designation	Assistant Professor
Qualification	B.Tech, M.Tech, UGC-NET-2019 JRF Qualified
Professional Exp.	4 Years Teaching \| 1 Year Industry
Research Interests	Computer Networks, Data Science
Registration Number	8056-220416-130520

Name	Mr. P. Ashok Kumar
Designation	Assistant Professor
Qualification	B.Tech (CSE), M.Tech (CSE), (Ph.D)
Professional Exp.	15.9 Years Teaching \| 1 Year Industry
Research Interests	Sentiment Analysis
Registration Number	8672-150415-124752

Name	Mr. Shafakhatullah Khan Mohammed
Designation	Assistant Professor
Qualification	M.Tech (CSE), (Ph D)
Professional Exp.	14 Years
Research Interests	Artificial Intelligence, Data Mining, and Network Security
Registration Number	0389-210921-192038

Name	Mr. Kiran Babu Kommu
Designation	Assistant Professor
Qualification	B.Tech (CSE), M.Tech (CSE)
Professional Exp.	13 Years
Research Interests	Computer Networks, Data Science
Registration Number	1715-040613-1716

Name	Mrs. Ch Vijayajyothi
Designation	Assistant Professor
Qualification	M.Tech (CSE), (Ph D)
Professional Exp.	12 Years
Research Interests	Machine Learning, Artificial Intelligence, Deep Learning, Analysis of Algorithms
Registration Number	5803-150418-161742

Name	Mrs. Pilligundla Niharika
Designation	Assistant Professor
Qualification	B.Tech (CSE), M.Tech (CSE), (Ph.D)
Professional Exp.	9 Years
Research Interests	Machine Learning
Registration Number	29150404-150258

Name	Mrs. B. Saritha
Designation	Assistant Professor
Qualification	B.Tech (CSE), M.Tech (CSE), (Ph.D)
Professional Exp.	8 Years
Research Interests	Machine learning, Data Science
Registration number	3373-170915-114707

Name	Mrs. Vagolu Vanaja
Designation	Assistant Professor
Qualification	B.Tech., M.Tech (CSE)
Professional Exp.	Teaching	Industry
	7 Years	8 Years
Research Interests	Computer networks, Data mining
Registration Number	6004-190108-114004

Name	Mr. Vanama Pavan Kumar
Designation	Assistant Professor
Qualification	B.Tech(IT)., M.Tech(CSE)
Professional Exp.	6 Years
Research Interests	Machine Learning, Big Data Analytics
Registration Number	98150331-122241

Name	Mr. Hari Krishna Mallu
Designation	Assistant Professor
Qualification	B.TECH (IT), M.TECH (CSE), (PhD), TSSET-2023
Professional Exp.	5 Years
Research Interests	Cryptography
Registration Number	8285-201108-114902

Name	Mrs. Turai Swathi
Designation	Assistant Professor
Qualification	B.Tech (CSE), M.Tech (CSE)
Professional Exp.	5 Years
Research Interests	Artificial Intelligence, Data Mining, and Network Security
Registration Number	4735-190827-134221

Name	Mrs. R Suruthi Sutharsana
Designation	Assistant Professor
Qualification	BE (IT), ME (IT), (PhD)
Professional Exp.	3.6 Years
Research Interests	Wireless sensor Network
Registration Number	4780-230324-132103

Name	Mrs. B. Sreelatha
Designation	Assistant Professor
Qualification	M.TECH
Professional Exp.	3 Years
Research Interests	Cyber Security
Registration Number	0934-170103-132946

Name	Mrs.K.Sukeerthi
Designation	Assistant Professor
Qualification	B.Tech(CSE), M.Tech(CSE)
Professional Exp.	2.6Years
Research Interests	Cloud Computing
Registration Number	7123-220707-140559

Name	Mr. Ashwani Attri
Designation	Assistant Professor
Qualification	B.Tech & M.Tech (CSE)
Professional Exp.	2.5 Years
Research Interests	Algorithms, Data Structures, Database Management System, Theory of Computation, Formal Language and Automata Theory, Computer Networks, Operation System, Computer Organisation and Architecture, Software Engineering
Registration Number	6132-240205-144227

Name	Mr. Sankul Revanth
Designation	Assistant Professor
Qualification	B.Tech & M.Tech (CSE)
Professional Exp.	2.4 Years
Research Interests	Data Science, Machine Learning
Registration Number	8733-210430-124306

Name	Mrs. Burra Anupama
Designation	Assistant Professor
Qualification	B.Tech(CSE)., M.Tech(CSE)
Professional Exp.	1 Year 8 Months
Research Interest	Cloud Computing
Registration Number	01150405-134753

Name	Mr. Pulkit Sharma
Designation	Assistant Professor
Qualification	B.E (CSE) , M.Tech (CSE)
Professional Exp.	Industry: 2 Years
Research Interests	Data Analysis and Machine Learning
Registration Number	4779-241023-151611

Name	Mr. Kalvacherla Kiran
Designation	Assistant Professor
Qualification	MSc(CS), M.Tech(CSE)
Professional Exp.	11 Years Teaching \| 2.4 Years Industry
Research Interests	Java, MachineLearning,Optimization Device Detection Using Machine Learning,DBMS
Registration Number	9132-160306-172210

Name	Mr. Y. V. S. Durga Prasad
Designation	Associate Professor
Qualification	B.Tech (ECE), M.Tech (Communication System), PGDM-Marketing., (Ph.D)
Professional Exp.	14.6 Years Teaching \| 2 Years Industry
Research Interests	Computer Networks
Registration Number	53150406-154658 (Others)

Name	Mr. J. Sampath Kumar
Designation	Associate Professor
Qualification	M.Tech., (Ph.D)
Professional Exp.	8 Years Teaching \| 3 Years Industry
Research Interests	Computer Networks/wireless communications
Registration Number	9591-150418-172929 (Others)

Name	Mr. Shaik Nagur Vali
Designation	Assistant Professor
Qualification	M.Tech
Professional Exp.	5.6 Years
Research Interests	Devops,AWS Cloud, Data Science
Registration Number	8328-240130-115807 (Others)

Name	Mrs. Ayesha Osmani
Designation	Assistant Professor
Qualification	M.Tech
Professional Exp.	2 Years
Research Interests	Cyber Security
Registration Number	8686-210701-155006

Name	Mr. S.Raja Sekhar Babu
Designation	Assistant Professor
Qualification	MCA., M.Tech (CSE)
Professional Exp.	10 Years
Research Interests	Java, Web Technologies, Operating Systems
Registration Number	3113-150409-121939

AI & DS

Name	Dr. S. Mani Kuchibhatla
Designation	Professor
Qualification	B.Tech., M.Tech (NIT-W), Ph.D (JNTUK)
Experience	20 Years
Research Interests	Power Quality Improvement, Flexible AC Transmission, PLC & SCADA
Registration Number	64150407-130107

Name	Dr. Atul Kumar Ramotra
Designation	Associate Professor
Qualification	B.E,M.E,Ph.D
Professional Exp.	4 Years
Research Interests	Data Mining, Machine learning, Deep learning
Registration Number	8547-240208-125650

Name	Mr. G. Suresh
Designation	Assistant Professor
Qualification	M.Tech (Ph.D – NITM)
Professional Exp.	9.5 Years
Research Interests	Biomedical Engineering, Artificial intelligence and machine learning, Materials Processing and Mechanical Behavior of Materials, Additive Manufacturing.
Registration Number	8554-160310-115647

Name	Mr. Saddala Anil
Designation	Assistant Professor
Qualification	M.Tech
Professional Exp.	2 Months
Research Interests	Machine learning and Deep learning
Registration Number	8938-240212-184050

Achievements

ACHIEVEMENTS

Faculty Achievements

S.NO.	Name
1	Dr. P. CHIRANJEEVI	Click here
2	Mrs. SOPPARI KAVITHA	Click here
3	KETAN ANAND	Click here
4	Mrs. THATIKONDA SUPRAJA	Click here
5	Ms.NIDUMOLU PRAGNATHY	Click here

Student Achievements

SNO	DATE	YEAR	ROLL NO	NAME	ACHIEVEMENT	PHOTO
1	03.08.2024	IV-I	21AG1A6728	K LAXMI PRASANNA	Selected in Zithara.ai company as Software Developer with package 5.0 to 6.0 LPA
2	03.08.2024	IV-I	21AG1A6753	PENMETSA LOKESH KARTHIK	Selected in Zithara.ai company as Software Developer with package 5.0 to 6.0 LPA
3	05.10.2024	IV-I	21AG1A6764	MEGHANA VIJAYARAGHAVAN	Selected in KORE.AI Company as Software Developer with package 8.5 LPA

Role of Honors

Department of CSE (Data Science)

S.No	Batch	Hall Ticket Number	Student Name	CGPA/Percentage
1	2020-2024	20AG1A6703	AENUGU AKSHITHA	9.26

Infrastructure

INFRASTRUCTURE

GPU SERVER CONFIGURATION

Hardware configuration	Dell OptiPlex 7080 Tower with 500w upto 92% efficiency PSU Intel Core i7 10700 10^th Generation 32GB DDR4 RAM, M.2 256SSD, 1TB HDD, NVIDIA GeForce RTX 2070 Super 8GB Dell wired keyboard, Windows 10 pro (64bit)
Operating System	Windows10, Ubuntu 16.04.
Open-Source Tools	Python 3.6.5, R-Language, OpenCV, C, C++, JAVA.
Licensed Tools	Oracle 12.1.0.2.0 with analytics.
Other resources	High Speed Internet, Projector, White Board, Intercom

Client system Configuration:

Hardware configuration	Intel i5 processor with 2.5GHz clock frequency, 4GB RAM, 500GB Hard Disk.
Operating System	Windows10, Ubuntu 16.04.
Open Source Tools	Python 3.6.5, R-Language, OpenCV, C, C++, JAVA.
Licensed Tools	Oracle 12.1.0.2.0 with analytics.
Other resources	High Speed Internet, Projector, White Board, Intercom

Course Structure

COURSE STRUCTURE

I B.Tech I-Semester

S. No	Course Code	Course Title
1	MA101BS	Mathematics – I
2	CH102BS	Engineering Chemistry
3	EE103ES	Basic Electrical Engineering
4	ME105ES	Engineering Workshop
5	EN105HS	English
6	CH106BS	Engineering Chemistry Lab
7	EN107HS	English Language and Communication Skills Lab
8	EE108ES	Basic Electrical Engineering Lab
9	MC109	Python Programming
10	MC110	Aptitude & Reasoning

I B.Tech II-Semester

S. No	Course Code	Course Title
1	MA201BS	Mathematics – II
2	PH202BS	Applied Physics
3	CS203ES	Programming for problem Solving
4	ME204ES	Engineering Graphics
5	PH205BS	Applied Physics Lab
6	CS206ES	Programming for problem Solving Lab
7	MC207ES	Environmental Science
8	MC208	Business English

II B.Tech I-Semester

S.No	Course Code	Course Title
1	CS301PC	Discrete Mathematics
2	CS302PC	Data Structures
3	MA305BS	Mathematical and Statistical Foundations
4	CS304PC	Computer Organization and Architecture
5	CS310PC	Advanced Python Programming
6	SM302MS	Business Economics & Financial Analysis
7	CS307PC	Data Structures Lab
8	CS311PC	Advanced Python Programming Lab
9	MC309HS	Gender Sensitization Lab

II B.Tech II-Semester

S.No	Course Code	Course Title
1	CS409PC	Formal Language and Automata Theory
2	CS410PC	Software Engineering
3	CS403PC	Operating Systems
4	CS404PC	Database Management Systems
5	CS405PC	Java Programming
6	CS406PC	Operating Systems Lab
7	CS407PC	Database Management Systems Lab
8	CS408PC	Java Programming Lab
9	MC409HS	Constitution of India

Syllabus

SYLLABUS

R20 Regulation – CSE(DS)

CSD R-20 III-I Syllabus

CSD R-20 III-II Syllabus

CSD R-20 IV-I Syllabus

CSD R-20 IV-II Syllabus

R22 Regulation – CSE(DS)

CSD R-22 I-I Syllabus

CSD R-22 I-II Syllabus

CSD R-22 II-I Syllabus

CSD R-22 II-II Syllabus

CSD R-22 III-I Syllabus

CSD R-22 III-II Syllabus

R24 Regulation – CSE(DS)

CSD R-24 I-I Syllabus

CSD R-24 I-II Syllabus

Events & Activities

Career Enhancement Programme – held on 06-05-2023

Kalam’s Institute of youth excellence is a Youth Transforming Mission to fulfil the Dr. A. P. J. Abdul Kalam Vision and Mission. Ace Engineering College in Collaboration with KIYE organised a one-day Career Enhancement Programme in ACE Engineering college on 06-05-2023.A total of 1200 students from 10 Engineering Colleges Participated in the Programme. Students are enlightened with broader aspects of career planning and entrepreneurship. The chief guest, Scientific advisor to Raksha Mantri Dr.G. Sateesh Reddy spoke about mind management, enhancement of creative skills with simple techniques and given day to day live examples. Special guest Dr.S. Somanth secretary Department of Space & Chairman ISRO gave valuable input about how to enhance skill in Advanced technologies and global Opportunities.

Program Report

TECHNICAL FEAST – held on 10/03/2023

Technical feast is organized by CODE. It is a coding competition conducted for both 2nd and 3rd year students. This test is based on Python programming & Quantitative aptitude and Reasoning

INDUSTRIAL VISIT TO T-HUB – held on 19/12/2022

T-Hub is creating impact for startups, corporations and other innovation ecosystem stakeholders-HUB helps the students who have ideas to implement for the society but who are financially weak. T-hub encourage them to implement their ideas

OPEN INTERACTION – held on 17/10/2022

Open interaction is organized by CODE. This open interaction is conducted for making students to come up with new thoughts and expressing their ideas with everyone.