DS, NLP & AI course

This comprehensive, free learning pathway is designed by top industry experts to lay a strong foundation in Data Science, Python, Natural Language Processing (NLP), and Artificial Intelligence (AI). These self-paced courses combine theory with practical application so that you can develop today’s in-demand skills. Whether you are a student or someone looking to enter the data-driven tech domain, these courses are perfect for building a strong foundation for your future career.

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About Course

This learning pathway will take on from Data Science fundamentals, key concepts, and applications, and an introduction to big data and ML. From there, you will gain hands-on programming skills in Python for Data Science to work with real datasets using Pandas and NumPy libraries. Then you can progress towards Natural Language Processing (NLP) with Python to process and analyze text to uncover meaningful insights. Finally, Artificial Intelligence (AI) course will introduce you to neural networks, TensorFlow, and building AI models. Read More

Skills you will learn

Data Science

Data Science Life Cycle

Data Science Applications

Big Data

Machine Learning

Deep Learning

R

R-Studio

Pandas

Numpy

Linear Regression

Logistics Regression

Spam Email Classifier

NLP

Text Mining

File Handling

Tokenization

Deep Learning

Tensorflow

Jupyter

Neural Networks

Single Layer Perceptron

Optimization Algorithms

Course Curriculum

Introduction to Data Science

1.1 Need for Data Science
1.2 What is Data Science
1.3 Life Cycle of Data Science
1.4 Applications of Data Science
1.5 Introduction to Big Data
1.6 Introduction to Machine Learning
1.7 Introduction to Deep Learning
1.8 Introduction to R & R-Studio

Introduction to Pandas

Introduction to Pandas, Pandas vs Numpy How to import Pandas in Python, Data-set in Python

Introduction to Machine Learning, Machine Learning Popular Myth, How does Machine Learn, Types of Machine Learning

What is Regression, Types of Regression, What is Linear Regression, Understanding Linear Regression,Mean Square Error, Logistics Regression Algorithm, Introduction to Logistics Regression, Why Logistics Regression, Spam Email Classifier, Demo Logistic Regression

  • What is Artificial Intelligence?
  • Difference b/w AI, Machine Learning and Deep Learning
  • Introduction to Machine Learning
  • Introduction to Deep Learning

  • Topology of Neural Networks
  • Deep Learning Frameworks
  • Introduction to Tensorflow
  • Introduction to Tensorflow 2.0

Hands-on:

  • Setting up Tensorflow in Jupyter Notebook

  • Limitations of Single Layer Perceptron
  • Feed Forward Network
  • Back Propagation
  • Optimisation Algorithms
  • Feedforward Neural Networks and Multi Layer Perceptron
  • Implementing a simple neural network

Hands-on:

  • Implementing a simple Neural Network using Tensorflow

1.1 Introduction to NLP and Text Mining
1.2 OS Module In Python
1.3 File Handling In Python
1.4 Natural Language Processing
1.5 Working with Word Files
1.6 Tokenization
1.7 Word_tokenize
1.8 Regexp Tokenizer
1.9 Blankline Tokenizer
1.10 Frequency Distribution

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FAQ's

What is the scope of data science professionals?

The global demand for data science professionals is projected to grow annually at 28% by 2026, with India leading South Asia’s AI transformation.

What is the outlook for data science in 2025?

The outlook for data science in 2025 seems extremely promising, with projections indicating a growth of around 35% this decade.

Data science is a rapidly growing field, with projected employment growth of around 35-36%.

If you are interested in a career in a data-driven environment, these courses are for you! It is for all students, recent graduates, or professionals looking to grow their skills in Data Science, Python, NLP, and AI.

No prior knowledge is required. A basic understanding of computers is sufficient.

No. These courses start from the basics and gradually build practical Python skills.

You will work with Python libraries like Pandas and NumPy to analyze real datasets.

You will learn Data Science concepts, Python programming, text processing with NLP, and building AI models. You will also get hands-on experience with popular tools like Pandas, NumPy, TensorFlow, and so much more.

These courses help you learn in-demand skills in one of the fastest-growing domains. Completing these courses will prepare you for entry-level roles in the data science industry.

Yes, all courses are self-paced, allowing you to learn at your own speed and revisit lessons as needed.

Yes, each course provides a free certificate upon completion, which you can share with potential employers or on professional platforms like LinkedIn.

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