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Course Details

Duration: 6 months|180 hours
Mode of Training: VILT

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Roadmap to Become Certified Data Science & Generative Ai Professional



Major Job Roles in Data Science & Generative AI

  • Data Scientist
  • Machine Learning Engineer
  • Deep learning Engineer
  • Natural Language Processing Engineer
  • Computer Vision Engineer
  • Generative AI Engineer
  • AI Ethics & Responsible AI Practitioner
  • Data Analyst
  • Business Intelligence Analyst
  • AI Product Manager
  • AI Research Scientist
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Roadmap to Become Certified Data Science & Generative Ai Professional



Benefits of Data Science & Generative Ai

Eligibilty

  • Any HSC Pass
  • Graduate
  • B.tech
  • Working Professional



High Demand Across Industies

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Diploma in Data Science & Generative AI Certificate



Curriculum of Data Science & Generative AI

    • Introduction to Data Science
    • Introduction to Machine Learning
    • Introduction to Deep Learning
    • Introduction to AI
    • Introduction to Generative AI
    • Difference Between Generative AI and Narrow AI
    • What is Data ?
    • Type Of Data ?
    • How To see Data ?
    • Statistics and Data Science
    • Measure of Central Tendency
    • Inferential Statistcs
    • Measure of Dispersion
    • Probability
    • What is Programming lang ?
    • Generation of Programming lang
    • Algorithm
    • Flowchart
    • Introduction to Python
    • History of Python
    • Application of Python
    • Python Installation
    • Python Programming mode
    • Python Variable, Data type ,Operator
    • Conditional statements
    • Loops
    • infinite statements
    • Python Data Structure List,Tuple,dictionary,Set
    • OOP
    • Object
    • Class
    • Inheritance
    • Polymorphism
    • Abstraction
    • Exception Handling
    • Database Connectivity
    • Data Analytics with python
    • Pandas
    • Numpy
    • MatplotLib
    • Seaborn
    • Lambda Expression
    • Built in modules
    • User define modules
    • Web Scraping
    • Case Studies
    • IPL Data Analytics
    • Web Scraping using selenium and perform Data Analysis
    • Make a TODO Applicationa
    • What is Machine Learning ?
    • What is AI ?
    • Type of Machine Learning
    • Data Collection and Preprocessing
    • Exploratory Data Analytics
    • Supervised ML
    • Linear Regression
    • Ridge Regression
    • Lasso Regression
    • Polynomial Regression
    • Regularization
    • Quantile Regression
    • Classification
    • Logistic Regression
    • K-nearest Neighbour
    • Support vector
    • Naive Bayes
    • Decision Tree
    • Evaluation Metrics
    • Clustering Unsupervised ML
    • K-Means
    • Mixture Models
    • Ensemble Learning
    • Bagging
    • Random Forest
    • Boosting
    • Gradient Boost
    • Ada Boost
    • XG Boost
    • Time Series Analysis
    • Naive Approach
    • Moving Average
    • Simple Exponential Smoothing
    • Holt's Linear Trend Model
    • Holt's Winter Model
    • ARIMA
    • SARIMAX
    • 10+ Business Case Studies
    • What is Deep Learning ?
    • Neural Networks
    • Keras, Tensorflow & Pytourch
    • Convolutional Neural Networks (CNNs)
    • Recurrent Neural Networks (RNNs)
    • Transfer Learning
    • Generative Adversarial Networks (GANs)
    • Text Classification
    • Named Entity Recognition
    • Sentiment Analysis
    • Language Generation
    • Image Classification
    • Object Detection
    • Image Segmentation
    • Face Recognition
    • Python Profile Report
    • Snorkel
    • MLBOX
    • TPOT
    • AutoKeras
    • Generative AI Applications in Market
    • What is LLM
    • Google Vertex
    • AWS SageMaker
    • Azure Open AI
    • Case Studies Discussion On Generative AI
    • Invoice Processing with AI
    • Customer Onboarding and KYC
    • IT Service Desk Support
    • Vendor Management and Compliance
    • Financial Report Generation
    • Route Optimization and Planning
    • Maintenance Scheduling
    • Traffic Management
    • Blockchain Implementation for Trade Finance
    • Introduction to SQL Server
    • Installation & type of Database
    • Explore Sample Database & Connectivity
    • What is RDBMS ?
    • Types of Keys
    • What is SQL ?
    • Using DDL / DML
    • Simple Queries.
    • Sub - Queries
    • Queries Using Joins
    • Using Aggregate Functions
    • Constraints
    • Working With Views
    • Stored Procedures
    • Triggers
    • Import/Export
    • Image Classification
    • Object Detection
    • Image Segmentation
    • Face Recognition
    • Python Profile Report
    • Snorkel
    • MLBOX
    • TPOT
    • AutoKeras
    • Generative AI Applications in Market
    • What is LLM
    • Google Vertex
    • AWS SageMaker
    • Azure Open AI
    • Case Studies Discussion On Generative AI
    • Invoice Processing with AI
    • Customer Onboarding and KYC
    • IT Service Desk Support
    • Vendor Management and Compliance
    • Financial Report Generation
    • Route Optimization and Planning
    • Maintenance Scheduling
    • Traffic Management
    • Blockchain Implementation for Trade Finance
    • Introduction to SQL Server
    • Installation & type of Database
    • Explore Sample Database & Connectivity
    • What is RDBMS ?
    • Types of Keys
    • What is SQL ?
    • Using DDL / DML
    • Simple Queries.
    • Sub - Queries
    • Queries Using Joins
    • Using Aggregate Functions
    • Constraints
    • Working With Views
    • Stored Procedures
    • Triggers
    • Import/Export

Frequently Asked Questions

Data Science is an interdisciplinary field that uses scientific methods, algorithms, processes, and systems to extract knowledge and insights from structured and unstructured data. It involves a combination of programming, statistics, domain knowledge, and data visualization to solve complex problems and make data-driven decisions.

Generative AI is a subset of artificial intelligence (AI) that focuses on creating models and algorithms capable of generating new data that resembles existing data. This includes tasks like generating text, images, music, and more. It's often used in creative applications, natural language processing, and content generation.

This course is suitable for a wide range of learners, including aspiring data scientists, machine learning engineers, and AI enthusiasts. It's also valuable for professionals looking to enhance their skills in data analysis, machine learning, and generative AI.

While there are no strict prerequisites, a basic understanding of programming (preferably in Python) and some familiarity with statistics and linear algebra will be helpful. Additionally, a curiosity about data and AI is essential.
In this course, you'll learn the fundamentals of data science, including data preprocessing, analysis, visualization, and machine learning. You'll also delve into generative AI techniques, such as generative adversarial networks (GANs) and recurrent neural networks (RNNs), to create AI-generated content like text and images.
The course will primarily use popular data science libraries in Python, such as NumPy, Pandas, Matplotlib, and scikit-learn. You'll also work with deep learning frameworks like TensorFlow or PyTorch for generative AI projects.
Yes, the course includes practical projects and assignments that will allow you to apply what you've learned. You'll work on real-world data analysis and generative AI projects to gain practical experience.

The course duration is 6 Month.

Yes.
Most courses provide support through discussion forums, email, or chat. You can also seek help from instructors or teaching assistants if available. It's essential to take advantage of these resources when you have questions or face challenges.
Completing a Data Science & Generative AI course can open up various career opportunities in data analysis, machine learning engineering, AI research, and more. Data scientists and AI professionals are in high demand across industries, making it a valuable skill set.
Yes, Most updated one tools and technology will be cover.
Yes, post completion of course.
  • 80% Attendance required
  • 100% assignment completion
  • 100% project completion on given deadline
  • 100% Career Service Session attendance
  • Good Grads in Internship
  • If any of above rule learner violate then learner will be debarred from job assurance policy.


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