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Data Science and Machine Learning Course

Basic
Data Science and Machine Learning Course

Duration: 3 - 3.5 Months
Mode: Online and Offline
Live Project & Internship: 15 days to 1 month
Hours: 2-3 hours per day, 5 days a week

Python Basics and Data Structures

✓ Dive into Python fundamentals
✓ Setup your Python environment.
✓ Learn Anaconda, Jupyter Notebook, and Google Colab
✓ Explore Python data structures: Numbers, Strings, Lists, Tuples, Sets, Dictionaries

Advanced Python Programming

✓ Work with files, modules, and packages
✓ Master control flow and decision-making
✓ Discover loop structures and control statements

Advanced Python Programming (Part 1)

✓ Get a grip on functions and their power
✓ Explore object-oriented programming (OOP)
✓ Understand classes and objects

Advanced Python Programming (Part 2)

✓ Go deeper into OOP concepts
✓ Handle exceptions effectively


Advanced Python Programming (Part 3)

✓ Dive into exception handling and user-defined exceptions
✓ Learn to work with JSON data

Exploratory Data Analysis (EDA) with Python

✓ Master Pandas, Numpy, Matplotlib, and Seaborn
✓Gain hands-on experience with detailed data analysis

Databases, Web Scraping, and Statistics

✓ Unlock the power of SQL
✓ Harness web scraping with BeautifulSoup
✓ Explore essential statistics for data science and machine learning integration.


Introduction to Machine Learning

✓ Enhance your grasp of statistics while also exploring its role.
✓ Embark on your machine learning journey

Machine Learning Algorithms (Part 1)

✓ Explore supervised learning algorithms
✓ Study Regression and Classification

Machine Learning Algorithms (Part 2)

✓ Delve into unsupervised learning and reinforcement learning
✓ Discover clustering and association algorithms

Real-world Projects with Kaggle

✓ Experience SVM, Naïve Bayes, KNN, and more on Kaggle. Hands-on projects featuring K-Means and PCA

HTML & CSS Basics

✓ Master HTML syntax and file structure
✓ Unveil the world of CSS: syntax, properties, colors, layouts, and more

Introduction to Django Web Framework

✓ Get started with Django for web development

Django with Machine Learning

✓ Integrate Django with your machine learning projects

Live Project Experience

✓ Apply your skills to a real-world project
✓ Solidify your knowledge through practical application
Course Details

Duration: 3 - 3.5 Months
Mode: Online and Offline
Live Project & Internship: 15 days to 1 month
Hours: 2-3 hours per day, 5 days a week

First Month

Week 1:

Python Basics and Data Structures
✓ Dive into Python fundamentals
✓ Setup your Python environment.
✓ Learn Anaconda, Jupyter Notebook, and Google Colab
✓ Explore Python data structures: Numbers, Strings, Lists, Tuples, Sets, Dictionaries

Week 2:

Advanced Python Programming
✓ Work with files, modules, and packages
✓ Master control flow and decision-making
✓ Discover loop structures and control statements

Week 3:

Advanced Python Programming (Part 1)
✓ Get a grip on functions and their power
✓ Explore object-oriented programming (OOP)
✓ Understand classes and objects

Week 4:

Advanced Python Programming (Part 2)
✓ Go deeper into OOP concepts
✓ Handle exceptions effectively


Second Month

Week 5:

Advanced Python Programming (Part 3)
✓ Dive into exception handling and user-defined exceptions
✓ Learn to work with JSON data


Week 6:

Exploratory Data Analysis (EDA) with Python
✓ Master Pandas, Numpy, Matplotlib, and Seaborn
✓Gain hands-on experience with detailed data analysis
matrix.

Week 7:

Databases, Web Scraping, and Statistics
✓ Unlock the power of SQL
✓ Harness web scraping with BeautifulSoup
✓ Explore essential statistics for data science and machine learning integration.

Week 8:

Introduction to Machine Learning
✓ Enhance your grasp of statistics while also exploring its role.
✓ Embark on your machine learning journey

Third Month

Week 9:

Machine Learning Algorithms (Part 1)
✓ Explore supervised learning algorithms
✓ Study Regression and Classification


Week 10:

Machine Learning Algorithms (Part 2)
✓ Delve into unsupervised learning and reinforcement learning
✓ Discover clustering and association algorithms

Week 11:

Real-world Projects with Kaggle
✓ Experience SVM, Naïve Bayes, KNN, and more on Kaggle. Hands-on projects featuring K-Means and PCA

Week 12:

HTML & CSS Basics
✓ Master HTML syntax and file structure
✓ Unveil the world of CSS: syntax, properties, colors, layouts, and more


Fourth Month

Week 13:

Introduction to Django Web Framework
✓ Get started with Django for web development

Week 14:

Django with Machine Learning
✓ Integrate Django with your machine learning projects

Week 15 -17

Live Project Experience
✓ Apply your skills to a real-world project
✓ Solidify your knowledge through practical application

CORS, aka Cross-Origin Resource Sharing, is a mechanism that enables many resources (e.g. images, stylesheets, scripts, fonts) on a web page to be requested from another domain outside the domain from which the resource originated.



Advance AI Engineering

Advanced
AI Engineering

Duration: 6 to 6.5 Months
Mode: Online and Offline
Live Project & Internship: 1 month
Hours: 3-4 hours per day, 5 days a week.




Same as basic data science and machine learning course

NLP Foundations

✓ Part 1: Introduction to NLP & Real-life Applications
✓ Part 2: Language Basics & Sentiment Analysis
✓ Part 3: Text Processing & Classification

Advanced NLP

✓ Part 1: Transformer Insights Discover Transformers, Huggingface, and RNNs in NLP.
✓ Part 2: Mastering NLP with Transformers Implement BERT, GPT-2. Excel in NLP tasks.

Interactive NLP Apps

✓ Part 1:Build NLP Web Apps: Streamlit
Streamlit's intro & setup
NLP integration & visuals
Easy deployment via Streamlit sharing
✓ Part 2: Create APIs: Django Rest Framework
DRF overview
NLP APIs, Serializers, ViewSets
Streamlit-DRF seamless integration

API Integration

✓ Deploy NLP models with Vertex AI.
✓ Utilize Huggingface, OpenAI, and Vertex APIs.
✓ Integrate the Transformer model on Vertex AI.


Advanced Techniques

✓ Unleash Language Models' power.
✓ Master neural machine translation.
✓ Create an emotion-aware chatbot with Language Models.


Live NLP Project

✓ Define, develop, and deploy an NLP project.
✓ Frontend-backend integration.
✓ Present your live NLP project.


Course Details

Duration: 6 to 6.5 Months
Mode: Online and Offline
Live Project & Internship: 1 month
Hours: 3-4 hours per day, 5 days a week.

Month 1 to 4

Week 1 to 17

Same as basic data science and machine learning course

Month 5

Week 18

NLP Foundations
✓ Part 1: Introduction to NLP & Real-life Applications
✓ Part 2: Language Basics & Sentiment Analysis
✓ Part 3: Text Processing & Classification

Week 19

Advanced NLP
✓ Part 1: Transformer Insights Discover Transformers, Huggingface, and RNNs in NLP.
✓ Part 2: Mastering NLP with Transformers Implement BERT, GPT-2. Excel in NLP tasks.

Week 20

Interactive NLP Apps
✓ Part 1:Build NLP Web Apps: Streamlit
Streamlit's intro & setup
NLP integration & visuals
Easy deployment via Streamlit sharing
✓ Part 2: Create APIs: Django Rest Framework
DRF overview
NLP APIs, Serializers, ViewSets
Streamlit-DRF seamless integration

Week 21

API Integration
✓ Deploy NLP models with Vertex AI.
✓ Utilize Huggingface, OpenAI, and Vertex APIs.
✓ Integrate the Transformer model on Vertex AI.

Month 6

Week 22

Advanced Techniques
✓ Unleash Language Models' power.
✓ Master neural machine translation.
✓ Create an emotion-aware chatbot with Language Models.


Week 23 - 25

Live NLP Project
✓ Define, develop, and deploy an NLP project.
✓ Frontend-backend integration.
✓ Present your live NLP project.


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