Institute Agenda :-
Study Materials ,Bag , ID Card Provide & course Non - Semester Pattern. Exam Scheduled July/August Month, Before 2 Months informed to Exam Appear students for their Hall Ticket Register.
(Note: Anytime agenda can change on the Management Basis.)
Learning Mode:- (Selection Type)
|
Type
|
Learning Mode
|
Classes Schedule & Timing
|
|
1
|
For Regular Learning
|
Timing 10 AM to 3PM
(Sunday/Govt & Local Holiday – Holiday)
[All Health Courses Applicable for Regular]
|
|
2
|
For Part-time Learning
|
Saturday Only (Timing 10AM to 4PM)
[Note: Health Dept Course only ]
|
|
3
|
For Distance Learning
|
Sequencely 7 days classes – only
(Timing 10AM to 4 PM)
[Note: Except Health Dept Course]
|
|
4
|
For Online Learning
|
Zoom Class (Monday to Friday)
& Meeting Discuss ( Timing 11 AM to 1PM)
[Note: Except Health Dept Course]
|
Course Overview:
These courses typically cover statistics, data preprocessing, machine learning algorithms, data visualization, and programming languages like Python. Programs range from 6 months to 2 years, with common topics including Python, machine learning, and deep learning, and often culminate in hands-on projects or a capstone project.
Course responsibilities:-
- Data analysis and insight generation: Use AI and machine learning to analyze large datasets, identify trends, and extract actionable business insights.
- Data preparation: Leverage AI for efficient data cleaning, transformation, and preparation, often using techniques like prompt engineering.
- Machine learning and modeling: Develop, refine, and deploy machine learning models to solve complex problems and create predictive analytics.
- Data visualization and reporting: Create dashboards, reports, and compelling visualizations to communicate findings and support data-driven decision-making.
- AI-powered solutions: Implement AI tools to create applications like chatbots, recommendation engines, and other AI-driven systems.
- Research and innovation: Stay updated on AI and machine learning advancements, research new techniques, and contribute to innovation in data modeling.
- Problem-solving: Apply analytical and statistical tools to solve problems across various industries, from finance to healthcare
Course Curriculum Components:
- Programming and Statistics: Introduction to programming languages like Python and R, and foundational statistical concepts.
- Data Management and Manipulation: Handling structured and unstructured data, data cleaning, and using databases with SQL.
- Data Visualization: Creating visualizations to communicate insights, using tools like Tableau, Power BI, and Python libraries (Matplotlib, Seaborn).
Advanced AI and machine learning components
- Machine Learning: Understanding and implementing supervised and unsupervised learning algorithms, such as regression, classification, and clustering.
- Deep Learning: Introduction to neural networks, including Convolutional Neural Networks (CNNs) for image data and Recurrent Neural Networks (RNNs) for sequential data.
- Natural Language Processing (NLP): Techniques for processing and understanding human language, including lexical, syntactic, and semantic analysis.
- Feature Engineering and Optimization: Techniques to prepare data for machine learning models, such as data normalization, dimensionality reduction, and feature selection.
Other important components
- Cloud Computing: Using cloud platforms like AWS, Azure, or GCP for data storage and analysis.
- Model Deployment: Learning how to deploy models into production using frameworks like Docker and Flask.
- Business Intelligence: Connecting analytics to business outcomes, including reporting and dashboard creation.
- Project and Case Studies: Applying learned skills to real-world problems through case studies and a final capstone project
- Job opportunities: Data Analyst, Data Scientist, Machine Learning Engineer, and AI Engineer. Graduates can also pursue roles like Business Intelligence Analyst, AI Consultant, and Computer Vision Engineer, with job prospects in various sectors like finance, healthcare, and e-commerce
Features of the Course :
During Training Period, OJT at Hospitals/Industrial/Companies (If applicable courses only)
Placement Guidance:
Those who are Regular and Part time candidate Assurance the Placement 100% throughout India based on the candidates and other online and distance Candidates. We will guide to the Placement and based on the Candidate’s willing.
- Further Clarification Contact: 88701 91125 , 96299 01300 , 73582 18375
