1. About ML and AI Group

The world we live in today is driven by data. This data is collected through Internet of Things (IoT) devices and stored them into the database where data analysis is performed to take some decisions using Artificial Intelligence and Machine Learning. This makes Machine Learning, Artificial Intelligence (AI) and IoT most in-demand technologies with a high requirement for professionals in the industry with relevant skills, training and hands on experience.

The Machine Learning group is started in 2017 with the aim to train our students in more demanding technologies and make them placeable in MNCs with handsome package. In the fourth semester Python module is run for all students and at the end of fourth semester an entrance test is conducted in order to form this group. All students of fourth semester can appear in this test and only top 30 students is selected as a member of this group. Next two years this group will go the regrous training on Machine learning, Deep learning and IoT

AI is pushing its edges in the technology world through its various fields like machine learning. It has fuelled the world with its breakthrough innovations. Machine learning has empowered systems without being actually coding it. Starting from the health care, financial services to the entertainment world, the concept has crept into all walks of life. Our real world examples in which google has showcased its revolutionary products like Google Assistant, Google camera. Smart reply feature in Gmail has been introduced where anticipated brief phrases are suggested to the user. Siri, Cortana, Netflix are all life changing examples in our daily use.


Training our students in this technology to make them technologically sound in the newest fields of this era is what we aim to achieve. We aspire to make our students stand apart in the crowd of techies in corporate or teaching world. Good placements in big corporate giants to whom our students can prove to be a great resource is the vision we have. Every year we are making a super-30 batch for creating a fresh mind workforce who will work dynamically & shape the new world. By conducting such courses we envisage that our students will be highly equipped with working knowledge of machine learning which will help them excel as a professional anywhere.

Why Machine learning

The evolution of machine learning has emerged from the pattern recognition & from the theoretical concept that computers can be made to learn without actually programming them to perform a specific task. The online suggestion system in the shopping sites, fraud detection , self driving google cars, applications like these has powered the concept of machine learning. Main reason for the resurgence in the momentum of this technology is its ability to cater in all sectors of society like transportation, security, retail, healthcare, government, defence etc. The increasing amount of data has sparked the need of analysing that data for knowledge discovery & its usage.

2. Module

Machine learning is a special branch of artificial intelligence aimed at making the systems dynamically react to given situations, predicting outcomes based on the past data. This module will provide skills required in building a strong career in machine learning. You will get to master basics of machine learning, diving more into deep learning algorithms with the help of a powerful programming language yet easy python to counter the real time problems in decision making.

  • Python and Statistical for ML & IoT
    • Python Basics
    • Jupyter notebook – Installation & function
    • Python functions, packages, conditional statement, loops
    • Working with data structures, arrays, list, dictionary, set, tuple, vectors & data frame.
    • Pandas, NumPy, Matplotlib, Seaborn
    • Class and object
    • File handling and Exception handling
    • Database connectivity
    • Real time projects
    • Descriptive Statistics
    • Linear and Logistic Regression
    • Random Variables
    • Expectation and Inequalities
    • Convergence of Random Variables
    • Estimating the CDF and Statistical Functions
    • Probability & Conditional Probability
    • Hypothesis Testing
    • Correlation Between Variable
    • Inferential Statistics
    • Probability Distributions - Types of distribution, Binomial, Poisson & Normal distribution
  • Machine Learning
    Supervised learning
    • Multiple variable linear regression
    • Logistic regression
    • Naive Bayes classifiers
    • Multiple regression
    • K-NN classification
    • Support vector machines
    • Decision Trees
    • Bagging
    • Random Forests
    • Boosting
    Unsupervised learning
    • K-means clustering
    • High-dimensional clustering
    • Hierarchical clustering
    • Dimension Reduction-PCA
  • IoT and Text Processing
    Text Processing
    • Natural Language Processing Introduction
    • Text pre-processing, Text Normalization
    • Text pre-processing, Text Normalization
    • Text Classification, Text Normalization, Bag of Words Model
    • Text Classification, Text Normalization, Bag of Words Model
    • Information Retrieval (IR)
    • Analyzing Term Similarity, Term Similarity, Document Similarity
    • Multinomial Naïve Bayes for text classification
    • Support Vector Machines for text classification
    • K-means Clustering for text classification
    • Topic Modeling, Latent Semantic Indexing, Latent Dirichlet Allocation
    • Latent Semantic Analysis, Text Rank
    • Semantic and Sentiment Analysis
    Internet of Thinks
    • Introduction of IoT and various sensors used in IoT
    • Study of wireless technologies
    • IoT Architecture & Protocol
    • Study of Arduino, Raspberry pi and Node MCQ
    • Connecting sensor to controller
    • Dashboard design
    • Google Assistance interface with IoT hardware
    • User voice commands over hardware
    • Web API dashboard setup.
    • Monitors sensors information on web application.
    • Store sensor information in database.
    • Real time projects
  • Deep Learning
    • Gradient Descent
    • Convolutional Neural Networks
    • Batch Normalization
    • Convolution, Pooling, Padding & its mechanisms
    • Hyper parameter tuning
    • Tensor Flow & Keras for Neural Networks & Deep Learning
    • Forward propagation & Backpropagation for CNNs
    • CNN architectures
    • Introduction to Perceptron & Neural Network
    • Activation and Loss functions
    • Deep Neural Networks
  • Real Time Projects
    This module will reserve for the real time projects implementation and research work. It will help student to implement some research paper and published them into the peer reviewed journals/conferences.
3. Career support
Internship Opportunity

SISTec will be providing internships for the machine learning batch students. Internships will be worth considering for a practical exposure of industry & also for good working knowledge of the concepts learnt in the classes. Students can avail the opportunity of internship from the college for better development & career profile.

Internship Info
S. No.Name Of CandidateCompany Batch
1AAMNA QURESHIInfotek Solution2017-2019
2AMRITA YADAVInfotek Solution
4POONAM SAXENAInfotek Solution
5NIKITA MALVIYAMeteorological Centre, India Meteorological Department (IMD), Bhopal
6PARUL SHRIVASTAVAMeteorological Centre, India Meteorological Department (IMD), Bhopal
7MOHAMMAD NOOR UL HASANMeteorological Centre, India Meteorological Department (IMD), Bhopal
8SOHEL AHMAD KHANMeteorological Centre, India Meteorological Department (IMD), Bhopal
9VISHAL SHANKARMeteorological Centre, India Meteorological Department (IMD), Bhopal
10PRAKASH DEVNANIMeteorological Centre, India Meteorological Department (IMD), Bhopal
S. No.Student NameCompany Name2016-2020
1Aayush KurupEmphasis Corp
2Harshal geeteEmphasis Corp
3KAPIL NEMAEmphasis Corp
4Muskan JainEmphasis Corp
5Shikha singhEmphasis Corp
6Vijay Raj SinghEmphasis Corp
7KeertiPRUDent System
8Abinash SinhaPRUDent System
9Bharat KabraPRUDent System
10Archit GuptaPRUDent System
Placement Opportunity

One stands a bright chance to grab the placement if he/she has an edge over other students. Machine learning being the hot cake in the market has already set its boots on the ground & has diversified job opportunities to get into. Analytics Engineer, data scientist, machine learning expert etc are various job profiles which have proved to be very lucrative & demanding in the present world & also will be the future of the world.

Pleacement Info
S. NONameCompany NameDesignation
1AAMNA QURESHIDiasparkAssociate Software Engineer
CognizantProgram Analyst
WiproAsst. Software Engineer
2AMRITA YADAVPraemineoMachine Learning Engineer
3DEEPSHIKHA SINGHNIITAsst. Software Engineer
5NIKITA MALVIYAPraemineoMachine Learning Engineer
6PARUL SHRIVASTAVAThink FutureAsst. Software Engineer
7POONAM SAXENAValue MomentumSoftware Trainee
8SOHEL AHMAD KHANPraemineoMachine Learning Engineer
10PRAKASH DEVNANINet2sourceAsst. Software Engineer
WiproProject Engineer
OpenTextAsst. Software Engineer
Faculty Experts
  1. Our mentors provide unparalleled guidance to the students, materials
  2. Receive proper one to one feedback for improvement
  3. A doubt resolution session is conducted accompanied with question answer session
4. Workshops
5. Meet the Mentor
Dr. Rajeev Gupta

Associate Professor, Department of CSE

Dr. Rajeev Kumar Gupta is a mentor of Machine Learning Group. He earned his M.Tech and Ph.D. from MANIT, Bhopal. Prior to joining SISTec, he was associated with NIT, Bhopal as Assistant Professor. He has more than seven years of teaching experience in various organisations for PG & UG courses of Computer Science & IT. His professional interest and research proficiency areas include Machine Learning, Deep Learning, IoT and Cloud Computing. He has been an efficient guide to several UG and PG students in their research work. He has delivered several expert talks and training sessions in the domain of Machine Learning and Cloud Computing. He is the recipient of BEST YOUNG RESEARCHER AWARD in RSRI conference on Recent Trends in Science and Engineering. For more detail, please visit

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