About Internship Program
● Most technological advancements as of now have components of Artificial Intelligence and Machine learning.
● This 45-day Artificial Intelligence and Machine Learning Course is remarkably planned by Kalinga University
with experts, to help you ace precisely the exact thing the Artificial Intelligence and Machine Learning needs
to position market requests.
Advantages
● Internship Program in AI and Machine Learning will assist you in pursuing a career in AI, Computer
Vision, Machine learning, and Deep Learning.
● Assemble ML models with NumPy and scikit-learn, construct and train supervised models for prediction
& binary classification tasks (linear, logistic regression).
● Build & train a neural network with TensorFlow to perform multi-class classification, & build & use
decision trees & tree ensemble methods.
● Apply best practices for ML development & use unsupervised learning techniques for unsupervised
learning including clustering & anomaly detection.
● Understand the definition of AI, its applications, and use cases, and explain terms like machine learning,
deep learning, and neural networks.
Who Should Attend
Beneficial for - Students of UG/PG Programs & Research Scholars of Information Technology and Computer Science,
etc.
Program Details
- Duration: 45 days
- Date: 23rd May to 6th July 2023
- Monday to Saturday
- Time: 10:00 am to 4:00 pm
- Venue: Kalinga University
- Program Fee: 10 ,000/-
Program Schedule
| Module-I Introduction to AI |
||
|---|---|---|
| S.No. | Topics | Duration |
| 01 | Introduction to AI, Specialized production system | |
| 02 | Intelligent Agent | |
| 03 | Search strategies | 5 days |
| 04 | Uninformed Search Algorithm | |
| 05 | Informed Search Algorithm |
| Module-II Problem Solving |
||
|---|---|---|
| S.No. | Topics | Duration |
| 01 | Problem solving methods | |
| 02 | Minimax Algorithm | |
| 03 | Alpha-Beta Pruning | 5 days |
| 04 | Heuristic functions -Hill Climbing | |
| 05 | Depth first and Breadth first, Constraint's satisfaction |
| Module-III Knowledge Representation |
||
|---|---|---|
| S.No. | Topics | Duration |
| 01 | Knowledge representation using Predicate logic | |
| 02 | Introduction to predicate calculus | 5 days |
| 03 | Resolution, use of predicate calculus | |
| 04 | Knowledge representation using other logic-Structured representation of knowledge | |
| 05 | First order logic |
| Module-IV Introduction to Machine Learning |
||
|---|---|---|
| S.No. | Topics | Duration |
| 01 | Machine Learning Applications | |
| 02 | Life cycle of Machine Learning | |
| 03 | Supervised Machine Learning | 5 days |
| 04 | Unsupervised Machine Learning | |
| 05 | Data Processing |
| Module-V Supervised Learning |
||
|---|---|---|
| S.No. | Topics | Duration |
| 01 | Regression Analysis | |
| 02 | Linear Regression | |
| 03 | Simple Linear Regression | |
| 04 | Multiple Linear Regression | 6 days |
| 05 | Backward Elimination | |
| 06 | Polynomial Regression |
| Module-VI Classification |
||
|---|---|---|
| S.No. | Topics | Duration |
| 01 | Classification Algorithm | |
| 02 | Logistic Regression | |
| 03 | K-NN Algorithm | 5 days |
| 04 | Support Vector Machine Algorithm | |
| 05 | Naive Bayes Classifier |
| Module-VIIMachine Learning Algorithms | ||
|---|---|---|
| S.No. | Topics | Duration |
| 01 | Decision Tree classifier, Support vector machine classifier | |
| 02 | Random forest classifier, Logistic Regression classifier | |
| 03 | Working with Unlabeled Data (Unsupervised Learning) | |
| 04 | Usage Unstructured data Predicting Elbow Method | 7 days |
| 05 | K -means Algorithm | |
| 06 | Regression Model | |
| 07 | Correlation and Covariance |
| Module-VIII AI ML Package & Practical Implementation |
||
|---|---|---|
| S.No. | Topics | Duration |
| 01 | Introduction to python programming | |
| 02 | Installation of packages in python | |
| 03 | Working with matplotlib | |
| 04 | Working with pandas | 7 days |
| 05 | Color tracking using OpenCV | |
| 06 | Edge detection using OpenCV | |
| 07 | Region of Interest using OpenCV |
Resource Persons
- Mr. Omprakash Dewangan
HoD Incharge, Dept. of Computer Science & Faculty of Information Technology
- Ms. Pooja P. Raj
Assistant Professor,
Dept. of Computer Science
REGISTER NOW
Note:
1. Accommodation facility is available on a chargeable basis: Rs 6,500/- for 45 days inclusive of Food (Air Cooled Room - 4 students/room, 3 Meals per day & other amenities).
2. Transport Facility available from common pickup point (Free).
Steps For Registration
Step 1:
Participants have to make payment on the given bank details
Account Name
Kalinga University
Bank Name
ICICI Bank
A/c No.
390701000010
IFSC Code No.
ICIC0003907
SWIFT CODE
ICICINBBCTS
Step 2:
Take screenshot of the payment & send it to
omprakash.dewangan@kalingauniversity.ac.in
Step 3:
Fill out the registration form with all the necessary information
To Register Scan the QR code
OrClick the Register Now button
Download Brochure
Account Name
Kalinga University
Bank Name
ICICI Bank
A/c No.
390701000010
IFSC Code No.
ICIC0003907
SWIFT CODE
ICICINBBCTS
