Machine learning and data science fields are gaining popularity and importance nowadays. The data science field uses techniques, algorithms, processes, and systems to extract information and insights from data. Machine learning is a subdivision of data science that deals with creating algorithms and models. These algorithms can learn patterns from data and make predictions. Data scientists use many tools and techniques to uncover meaningful insights from the data. They collect and clean data, then interpret it to make informed decisions.  Tasks like classification, regression, clustering, and recommendation are done by making use of machine learning algorithms. A wide range of industries like healthcare, finance, retail, manufacturing, etc. use machine learning and data science for enhanced decision-making.

In the 21st century, data science ranks among the most sought-after skills; Kerala cannot escape this trend. Amidst expanding companies seeking talented data experts, professionals with keen abilities in data science have a significant appeal within the workforce of this location. Offered through the GALTech School of Technology, the Data Science and Machine Learning Course aims to equip aspiring data scientists with essential knowledge and abilities. Insightful instruction from seasoned practitioners lies at the core of this curriculum. By participating in actual projects, you acquire professional skills vital for employment.

Data Science

Python for Data Science

Offering versatility and widespread application, Python proves an adaptable language in the domain of data science. By offering a myriad of libraries and tools, it becomes a premier choice for handling everything from data manipulation to visualization. Libraries including pandas, NumPy, and Matplotlib enable seamless data management and visualization, while scikit-learn, TensorFlow, and PyTorch allow for the creation and training of sophisticated machine learning models. Merging these aspects creates a suitable environment for newcomers and seasoned data experts, alike, to extract meaningful insights and shape informed decisions via Python.

If you are looking for a comprehensive and practical data science course in Kerala, then GALTech School of Technology is the perfect choice for you. The Data Science and Machine Learning Course from GALTech School of Technology is the perfect way to launch your career in data science. With the skills you will learn in this course, you will be well-positioned to land a job in this growing field.

Basic

DATA SCIENCE & MACHINE LEARNING COURSE

Document

Course Details

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

Week 01

Week 01

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 02

Week 02

Advanced Python Programming

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

Week 03

Week 03

Advanced Python Programming (Part 1)

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

Week 04 - 05

Week 04

Advanced Python Programming (Part 2)

✓ Go deeper into OOP concepts
✓ Handle exceptions effectively

Week 05

Advanced Python Programming (Part 3)

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

Week 06 - 07

Week 06

Exploratory Data Analysis (EDA) with Python

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

Week 07

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 08 - 09

Week 08

Introduction to Machine Learning

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

Week 09

Machine Learning Algorithms (Part 1)

✓ Explore supervised learning algorithms
✓ Study Regression and Classification

Week 10 - 11

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

Week 12

HTML & CSS Basics

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

Week 13 - 14

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 14 - 17

Week 14 - 17

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

ADVANCED AI ENGINEERING

Document

Course Details

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.

Week 01 - 17

Week 01 - 17

Same as basic data science and machine learning course

Week 18

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

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

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

Week 21

API Integration

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

Week 22

Week 22

Advanced Techniques

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

Week 23 - 25

Week 23 - 25

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.


Document

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.


Data Science

Why GALTech?

Classes from Industry Experts

Project-based

Job-focused

Placement Assistance

Internship Programs

HD Video Recordings

Weekly Projects & Assignments

Industry-specific Curriculum

Peer-to-peer

Self-paced

Certification

Affordable Fees

Data Science

Who can join?

Graduates

Students who has completed their science degree. BSC, MSC etc.

Professional Graduates

Students who has completed their BTech, BE, MTech, MCA, Diploma in CS/IT etc.

Working Professionals

Software Engineers or Developers working in IT field planning to switch their career or add new skillsets.

Common Queries

Frequently Asked Questions

The course is designed to provide a comprehensive understanding of data science and machine learning concepts. It covers topics such as data analysis, machine learning algorithms, data collection, web scraping, and advanced techniques like natural language processing and deep learning.

You’ll learn essential skills such as data analysis with SQL, web scraping using Beautiful Soup, building machine learning models, and working with natural language processing techniques. The course also covers advanced topics like deploying models and integrating APIs.

Some basic programming experience will be helpful, but the course is designed to accommodate learners with various levels of experience. It starts with fundamentals and progresses to more advanced concepts.

Throughout the course, you’ll work on a variety of projects. Examples include building a sentiment analysis model, predicting restaurant ratings based on reviews, and developing a next-generation chatbot using advanced NLP techniques.

The recommended time commitment can vary, but generally, you should expect to spend several hours per week on lectures, working on assignments, and completing projects effectively.

Absolutely. The course is designed to equip you with practical skills that are highly relevant in today’s data-driven world. You’ll be able to apply what you’ve learned to real-world data analysis and machine-learning projects.

Completing this course can open doors to various roles in data science, machine learning engineering, data analysis, and AI development. These fields are in high demand across industries.

Apply Now

Data Science and Machine Learning Course in Kerala

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