Data Science and AI

Teacher

Ms.Indira Kumar

What Will I Learn?

Python
Statistics and EDA
SQL
Power BI
Data Science
Artificial Intelligence
Tableau
Advanced Excel
Value Added Sessions
Capstone Project
Live Project
Resume Preparation
Mock Interviews

Requirements

64-bit PC with 8GB/16GB RAM capable of processing 500MB data (recommended).
Or a Mac capable of capable of processing 500MB data (must support Metal).
About 25GB of free disc space.

Description

🚀 Break Into Data Science & AI – No Coding Experience Needed!

Data Science and Artificial Intelligence are transforming industries worldwide, but you don’t need to be a programmer to get started! Our specially designed course empowers absolute beginners and non-tech professionals to build expertise in Data Science & AI from scratch – no prior coding experience required!

Why This Course?

✅ No Technical Background Required – We start with the absolute basics, ensuring you understand every concept without any prior knowledge of coding or statistics.

✅ Hands-On Learning – Learn by doing! Work on real-world projects, gain practical experience, and build a portfolio to showcase your skills.

✅ Simplified Learning Approach – Complex topics are broken down into simple, easy-to-understand explanations so that anyone can grasp them.

✅ Comprehensive Curriculum – From understanding data analysis and visualization to implementing AI-driven solutions, we cover everything you need to become job-ready.

✅ Learn at Your Own Pace – The course includes high-quality, professionally recorded lessons with handwritten subtitles so you can pause, rewind, and learn at your convenience.

✅ Exclusive Community Support – Join a thriving community of like-minded learners, engage in discussions, and get guidance from instructors and fellow students.

What will you learn?

📊 Data Science Fundamentals – What is Data Science, and how can it help businesses make smarter decisions?

📈 Data Analytics & Visualization – Learn how to analyze and present data using simple, intuitive tools.

🤖 Introduction to AI & Machine Learning – Understand AI concepts, how machines learn, and how AI is used in everyday applications.

💡 Real-World AI Applications – Explore AI-powered tools and platforms without writing a single line of code.

🚀 Career & Business Opportunities in AI – Discover how Data Science & AI can enhance your career or business, whether you're in marketing, finance, healthcare, or any other field.

Who Is This Course For?

🔹 Complete Beginners – If you have ZERO experience with AI, coding, or data science, this course is for you!

🔹 Business Professionals – Want to make data-driven decisions but don’t know where to start? We’ve got you covered.

🔹 Entrepreneurs & Managers – Learn how AI can give your business a competitive edge – without hiring a data scientist.

🔹 Anyone Curious About AI – If you’re excited about AI and want to explore its potential, this is the perfect starting point.

Get Started Today!

The world is changing, and AI is leading the revolution. Don’t let a lack of technical skills hold you back! Join thousands of learners who have taken their first step into the world of Data Science & AI without any prior experience.

📌 Enroll now and take charge of your future with AI!

Curriculum For This Course

340 Lectures

42:57:42

Python 12 Lectures 32:01:29

Introduction to Python and Its Advantages01:01:39
Introduction To IDEs00:21:43
Variable And Its Rules02:07:48
Operators02:01:39
Data Types05:23:00
Functions And Parameters03:09:40
Exception Handling and File Handling03:00:03
Regular Expressions03:00:03
Pandas03:00:03
Numpy03:00:03
Matplotlib03:00:03
Seaborn03:00:03
os03:00:03

Statistics - EDA 12 Lectures 27:26:45

Introduction To Statistics00:10:39
Data Collection, Data Preparation and Inference01:01:43
Sampling, Types Of Sampling and Varinace in Sample02:07:48
Data Types02:01:39
Descriptive Statistics03:45:12
Data Distributions03:09:40
Probability Theory02:00:03
Central Limit Theorem01:00:03
Confidence Interval03:00:03
Hypothesis Testing02:00:03
Correlation and Covariance02:00:03
Data Preparation06:00:03
Mini Project10:00:03

SQL 12 Lectures 58:00:36

Instroduction to DataBase01:01:39
Understanding The Architecture of the DataBase02:01:43
Data Types In SQL02:07:48
Command Types in SQL06:01:39
Operators in SQL03:12:00
Constraints in SQL06:09:40
Joins05:00:03
Sub Queries04:00:03
Index, Views and Union02:00:03
Common Table Expression04:00:03
Window Functions03:00:03
Triggers04:00:03

Power BI 11 Lectures 30:01:12

Get Or Connect To Data02:00:13
Profile and Clean The Data03:01:43
Transform and Load The Data03:07:48
Design And Implement The Data Model01:01:39
Create Model Calculation Using Data Model02:23:12
DAX06:09:14
Optimize Model Performance02:09:40
Enhance Reports For Usability And Story Telling03:00:03
Identify Patterns And Trends03:00:03
Create And Manage WorkSpaces and Assets03:20:03
Secure and Govern Power BI Items03:00:03

Data Science - Mathematical Foundation 7 Lectures 08:21:29

Function01:05:23
Differentiation01:45:39
Linear and Non-Linear Algebra01:08:43
Vector and Matrix00:40:39
Maximum Likelyhood Estimation00:43:00
Entropy00:09:40
Revision03:00:03

Data Science - Unsupervised Learning 07 Lectures 22:01:29

Hierarchical Clustering03:48:39
K-Means Clustering03:01:43
Dimension Reduction - PCA03:07:48
Dimension Reduction - SVD03:01:39
Association Rules03:00:00
Recommendation Engine03:00:00
Network Analytics03:30:00

Data Science - Supervised Learning 07 Lectures 29:01:39

K - Nearest Neighbour04:01:39
Linear Regression05:01:43
Logistic Regression04:47:48
Support Vector Machine02:01:39
Decision Tree04:06:23
Ensemble Techniques06:09:40
Naive Bayes04:00:03

Data Science - Natural Leanguage Processing 08 Lectures 26:01:25

Basics Of NLP03:01:39
Dara Preprocessing in NLP03:35:43
Feature Engineering in NLP02:07:48
Building Pipeline03:01:39
Web Scrapping03:23:00
Advancements in NLP03:09:40
Naive Bayes - Classification03:09:40

Data Science - Time Series Analysis 07 Lectures 04:21:59

Survival Analytics01:30:39
Time Series - Data Types00:20:43
Forecasting Strategies01:07:48
Components Of Time Series00:45:39
Data Partition00:29:23
Forecasting Of Errors00:31:40
Seasonal Index00:25:03

Data Science - Deep Learning 07 Lectures 29:56:21

Introduction To Deep Learning01:41:39
Anatomy Of Neural Networks03:51:43
ANN - Regression03:07:48
ANN - Classification03:01:39
CNN - Object Classification02:51:23
CNN - Object Detection03:09:40
RNN - Prediction, Sentiment Analysis04:24:03

Introduction To AI 10 Lectures 17:01:47

Neuron and Inspiration Behind Neuron02:01:39
Anatomy Of Neural Network02:01:43
Activation Functions02:07:48
Loss Functions02:01:39
Back Propogation - Gradient Descent02:23:25
Optimization Function02:09:40
Convolutional Layer01:09:40
Pooling, Batch Normalization01:19:40
Filters And Feature Maps01:00:03
Vector Embeddings02:00:03

GRU, LSTM & Bi-Directional LSTM 5 Lectures 03:34:20

Gated Recurrent Network01:39
Long and Short Term Memory01:43
Bi-Directional LSTM07:48
Hyper Parameter Tuning01:39
Challenges in Deep Learning2 pages
When Gradient Goes Wrong Direction09:40
Learning Rate Adaption00:03

Computer Vision & Image Processing 10 Lectures 16:38:07

Structure Of An Image And Basics02:01:39
Image Processing Using OpenCV02:01:43
Edge Detection Techniques02:07:48
Non-Maximum Supression00:15:39
Hysterisis Threshold00:20:00
Image Gradient02:09:40
Effects Of Noise02:00:03
Variuos Types Of Filters02:00:03
Image Sampling Techniques02:00:03
Image Aliasing and Anti Aliasing02:00:03
Variuos Types Of Filters02:00:03
Variuos Interpolation02:00:03

Image Segmentation - Semantic, Instance and Panopic 13 Lectures 04:01:15

Image Classification Vs Object Detection Vs Image Classification01:39
OCR01:39
YOLO Models01:43
Variuos RCNN Models07:48
YOLO Vs RCNN01:39
Semantic Segmentation2 pages
Instance Segmentation09:40
Panopic Segmentation00:03

Squence To Sequence Models 04 Lectures 06:01:15

Introduction To Seq2Seq Model02:01:39
Variants Of Seq2Seq Models01:01:43
HuggingFace02:07:48
Model Evaluation02:01:39
Fine Tuning Of Seq2Seq Models02:23:12
Fine Tuning Methods01:09:40

Transformers 13 Lectures 14:01:15

Introduction To Transformers00:10:39
Understanding The Components Of Transformers03:01:43
LLMs Using Transformers02:07:48
Encoder Only And Decoder Only Models01:01:39
Fine Tuning(LoRA, QLoRA)02:12:34
Model Evaluation01:09:40
Lets Build A Chatbot04:00:03

Generative Adversarial Networks 13 Lectures 03:01:15

Introduction To GAN01:39
Components Of GANs01:43
Types Of GANs07:48
Application Of GANs01:39
Implementation Of GANs2 pages
Capstone Project09:40

Auto Encoders and Variational Auto Encoders 13 Lectures 03:01:15

Introduction To Encoders01:01:39
Math Behind The Encoders01:01:43
Variational Auto Encoders01:07:48
Auto Encoder Vs Variational Auto Encoder01:01:39
Implementation Of Auto Encoders01:10:12
Implementation Of Variational Auto Encoders01:09:40
Capstone Project02:00:03

Speech Recognition 03 Lectures 04:01:15

Introduction To Speech Recognition00:21:39
Packages For Speech Recognition01:01:43
Implementation Of An Application01:37:48
Building Song Transcriptor Application01:21:39

Value Added Sessions 13 Lectures 150:01:15

Advanced Excel40:01:39
Tableau40:01:39
Reinforcement Learning3:01:39
Deep-Q Learning2:01:43
PyTorch03:07:48
TensorFlow03:01:39
LangChain03:01:30
Langgraph03:09:40
PySpark09:00:03
AWS06:00:03
Azure06:00:03
Fast API03:00:03
Streamlit02:00:03
Basics Of Web Developement04:00:03
OpenAI API03:00:03

Instructors

4.7 .7 Average rating
25,182 Reviews
11,085 Students
2 Courses

(4 votes)

Profesional Program In Data Science And Artificial Intelligence

Teacher: Mr. IndiraKumar Anbu

Hi! I'm Indira Kumar, a passionate Data Scientist with four years of experience in AI, machine learning, and data-driven solutions. Over the years, I've worked on complex AI models, optimized data pipelines, and developed cutting-edge applications that drive real business impact. Now, I'm embarking on a new journey—building an institution that leverages the power of AI to transform industries. Our mission is to help businesses harness the true potential of data, from predictive analytics to intelligent automation. Having worked with diverse datasets and industries, I’ve gained deep expertise in developing scalable AI solutions, from computer vision models to NLP-based applications. I believe in making AI accessible, efficient, and impactful. Through my work, I’ve mentored aspiring data scientists, collaborated with industry leaders, and built AI solutions that redefine possibilities. My goal with this new venture is to empower businesses and individuals with the best AI-driven insights and solutions.

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