Certificate in Artificial Intelligence and Machine Learning

Live

Fee: ₹30,000

Dr. Priti Maheshwary | Professor FSA

This course is designed for aspiring professionals looking for a career transition into the AI & ML space, who have basic programming skills, interest in technology and an analytical bent of mind. The learners will get acquainted with the fundamentals of Python , Machine Learning , Deep Learning , Natural Language processing , Computer Vision and Deployment at cloud platform.

Objectives

How to discover patterns in the user data and then make predictions based on these and intricate patterns for answering business questions and solving business problems

How to make machines learn using different ML algorithms .

How to develop interaction between humans and computers using natural language.

How to enable computers and systems to derive meaningful information from digital images, videos and other visual inputs .

How deploying an application through one or more hosting models—software as a service (SaaS), platform as a service (PaaS) and/or infrastructure as a service (IaaS) can be implemented.

https://youtu.be/MAqWzsKg-PY

What Will You Learn

With this course, you will learn : Python programming , Python libraries Numpy, Pandas , Matplotlib , Seaborn , Supervised Machine Learning , Unsupervised Machine Learning , Deep learning , Natural Language Processing , Computer Vision , Deployment on AWS cloud.

Skills you will gain

Programming Languages Python

Linear Algebra, Calculus, Statistics ,Applied Math and Algorithms

Machine Learning ,Neural Network Architectures , Audio and Video Processing

Computer Vision,Signal Processing Techniques ,cloud deployment basics

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Curriculum

PAPER 1- Introduction to Artificial Intelligence & Machine Learning
- Paper 1- Live Lecture 1
- Introduction to Artificial Intelligence
- Introduction to machine Learning
- Introduction to Deep Learning
- Real World Applications of AI/ML
- Ethics in Machine Learning
- Evaluation of Machine Learning codes

PAPER 2- Mathematics and Statistics for AI/ML
- Python Statistics Libraries
- Vectors
- Matrix
- Probability and Statistics
- Descriptive Statistics
- Random Numbers

PAPER 3 - Introduction to Python
- Introduction to Python
- Python Language Syntax & Data Types
- Conditions/Loops
- Libraries in Python
- Numpy
- Panda
- Data Story Telling
- Data Acquisition
- Data Cleaning and Preprocessing
- Data Manipulation Using Excel
- Data Manipulation using MySQL
- Advance Queries
- Data Visualization Using Python
- Data Visualization Using PowerBI

PAPER 4- Supervised & Unsupervised learning
- Supervised & Unsupervised learning
- Multiple Linear Regression
- Logistic Regression
- SVM
- KNN
- Random Forest Algorithm
- Naïve Bayes
- Types of Learning
- Clustering in Machine Learning
- K means Clustering
- Elbow Method for optimal value of k in K means
- Mean-shift Clustering
- Fuzzy Clustering
- Internal Assessment

PAPER 5 - Reinforcement Learning and Story Telling
- Introduction Reinforcement Learning
- Q-Learning Algorithms
- Introduction to Thompson Sampling
- Genetic Algorithm for Reinforcement Learning
- SARSA Reinforcement
- Q-Learning in Python Example
- Story Telling

PAPER 6- Tensor Flow PyTouch
- Tensor Flow Basic
- Tensor Flow Perceptron
- CNN in Tensor Flow
- RNN in Tensor Flow
- Introduction to Keras
- Distributed Computing Tensor flow
- Multi Layer Perceptron Learning
- Image Recognition using Tensor Flow
- The Role of Cloud Computing in Artificial Intelligence
- Cloud deployment ,its types and popular service providers
- Building the model using jupyter notebook
- Export the model using Pickle
- Build a Flask website to serve the model
- Steps in Deploying model to aws
- Introduction to GIT and GITHUB ,installation and creating repository
- Internal Assessment

PAPER 7- Natural Language Processing
- Natural Language Processing
- Steps to Train Dataset for NLP
- Text Preprocessing in Python
- Removing stop words with NLTK in Python
- Tokenize text using NLTK in Python
- Restaurant Reviews Project

PAPER 8 -Artificial Neural network
- Introduction to Artificial Neural Networks
- Structure of Neural Network
- Characteristics of ANN
- Types Neural Network
- Implementing ANN Training process in Python

PAPER 9- Computer Vision
- Introduction to Computer Vision?
- Computer vision and Image processing
- Installing useful packages
- Introduction to OpenCV
- Reading , Writing and displaying an image
- Color Space Conversion
- Edge Detection
- Face Detection
- Eye detection
- Internal Assessment

Instructor

Dr.Priti Maheshwary

Professor FSA

IT, Computer Science

Presently working in Future Skill Academy. Involved in Computer Science and Engineering for over 20 years in higher education and training. Her career has included various software development projects, teaching, research, and administrative roles. She enjoys teaching and looking into how to improve the student learning experience. Published around 50 research papers in refereed journals and conferences, 7 book chapters, and 6 Patents. 8 PhD thesis completed under her guidance in the field of Internet of Things, Smart Cities, Ubiquitous Computing, Wireless Sensor Network, VANET, Image Processing specialized in Satellite Images, AI/ML & Deep Learning, and Cyber Security. Also done more than 10 projects in the field of Research and Consultancy.

4 1045 1100 Learners

Dr. Pooja Bijlani

Trainer (Subject Matter Expert) Future Skill Academy

AI ML, Data science, Full Stack Web Development, Full Stack Java Development

Presently she is working as an IT Trainer (Subject Matter Expert) at Future Skill Academy, AISECT, Bhopal. She is having over 15 years of academic and research experience. Expert in Programming Languages C,C++,Python, Java, React Spring Boot, Artificial Intelligence, Machine Learning and Data Science. Students accoladed her programming language teaching skills. Having experience in number of End to End projects in Natural language Processing, Computer Vision and Python Desktop Application GUI. Web Designing.

4.9 968 1087 Learners

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