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Advance Data Science & Data Analytics

Advanced Data Science & Data Analytics is a comprehensive, industry-oriented program designed to train learners in analyzing, interpreting, and extracting insights from data. The course covers data analytics, data visualization, statistical analysis, machine learning concepts, and real-world data-driven decision-making, preparing learners for advanced analytics and data science roles.

To enroll in this course, please contact the Admin
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Course Overview

The Advanced Data Science & Data Analytics course provides in-depth knowledge of the complete data lifecycle, from data collection and cleaning to analysis, visualization, and predictive modeling. Learners will work extensively with Python and data analysis tools to handle large datasets and generate meaningful insights.

The program includes data analytics techniques, exploratory data analysis (EDA), and data visualization using charts and dashboards to support business decisions. Learners will also be introduced to machine learning algorithms, statistical modeling, and model evaluation techniques.

With a strong emphasis on hands-on projects, case studies, and industry use cases, this course prepares learners for roles such as Data Analyst, Data Scientist, Business Analyst, or Machine Learning Engineer and equips them with skills required in data-driven industries.

Schedule of Classes

Course Curriculum

13 Subjects

MySQL for DataAnalytics/Data Science - 5 weeks

1 Exercises1 Learning Materials

MySQL-For DA

MySQL for DA-DS

PDF

MySQL Exercise

MySQL Exercise

Exercise

Advance Excel ( Data Analytics ) - 3 weeks

1 Exercises1 Learning Materials

Advance Excel for Data Analytics

Advance Excel for Data Analytics

PDF

Adv. Excel Exercise

Adv. Excel Exercise

Exercise

PowerBI - 3 weeks

1 Learning Materials

Power Bi notes

PowerBi Notes

PDF

PowerBI Exercise

Tableau - 3 weeks

1 Exercises1 Learning Materials

Tableau Notes

Tableau Notes

PDF

Tableau Exercise

Tableau Exercise

Exercise

Python for ( Data Analytics / Data Science ) - 5 weeks

1 Exercises1 Learning Materials

Python for Data Analytics notes

Python for Data Analytics notes

PDF

Python Exercise

Python Exercise

Exercise

Basic & Advanced Statistics ( Data Analytics ) - 1 Week

2 Exercises

Basic Statistics

Basic Statistics Exercise

Exercise

Advanced Statistics

Advanced Statistics Exercise

Exercise

AI + NLP - 3 weeks

1 Exercises

NLP & AI Exercise

NLP & AI Exercise

Exercise

Deep Learning - 3 weeks

1 Exercises

Deep Learning Exercise

Deep Learning Exercise

Exercise

Data Science + Machine Learning - 5 weeks

11 Exercises11 Learning Materials

1. Driving The World of Data

1. Driving the World of Data

PDF

Driving The World of Data Exercise

Exercise

2. Exploratory Data Analysis

2. Exploratory Data Analysis

PDF

Exploratory Data Analysis Exercise

Exercise

3. Basic Statistics

3. Basic Statistics

PDF

Basic Statistics Exercise

Exercise

4. Advanced Statistics

4. Advanced Statistics

PDF

Advanced Statistics Exercise

Exercise

5. Deep Learning

5. Deep Learning

PDF

Deep Learning Exercise

Exercise

6. Natural Language Processing

6. Natural Language Processing

PDF

Natural Language Processing Exercise

Exercise

7. Time Series Forecasting

7. Time Series Forecasting

PDF

Time Series Forecasting Exeercise

Exercise

8. ChatGPT

8. ChatGPT

PDF

ChatGPT Exercise

Exercise

9. Introduction to Web Scraping

9. Introduction to Web Scraping

PDF

Introduction to Web Scraping Exercise

Exercise

10. Machine Learning

10. Machine Learning

PDF

ML Excercise

Exercise

11. Artificial Intelligence

11. Artificial Intelligence

PDF

Artificial Intelligence Exercise

Exercise

Aptitude Exam (Preparation)

4 Learning Materials

Lecture 1

Lecture 1

Video
00:19:04

Lecture 2

Lecture 2

Video
00:39:52

Lecture 3

Lecture 3

Video
00:31:10

Lecture 4

Lecture 4

Video
00:40:28

Github

1 Exercises5 Learning Materials

Lecture 1

L1-Intro To Git & Github

Video
00:28:18

Lecture 2

L2-Git Commands & Other Concepts

Video
00:41:12

Lecture 3

L3-Commiting & Adding Files

Video
00:38:38

Lecture 4

L3-Concept Of Merging And Merge Conflict

Video
00:12:11

Lecture 5

L4-Posting

Video
00:15:49

Git & Github Exercise

Git & Github Exercise

Exercise

English Communication

5 Learning Materials

Lecture 1

L1-Process Of Communication

Video
00:32:38

Lecture 2

L2-Barrier of Communication

Video
00:36:18

Lecture 3

L3-Telephone Techinique & Job Application

Video
00:33:38

Lecture 4

L4-Pronunciation

Video
00:33:38

Lecture 5

L5-Group Discussion

Video
00:34:19

Prompt Engineering

15 Learning Materials

Lecture 1

L1-Foundation For Beginner

Video
00:19:56

Lecture 2

L2-Role & Context Prompting

Video
00:21:56

Lecture 3

L3-Table, List & Frameworks

Video
00:24:56

Lectuer 4

L4-Teaching AI With Examples

Video
00:19:13

Lecture 5

L5-Clear Instruction

Video
00:15:17

Lecture 6

L6-Step-By-Step Reasoning

Video
00:28:11

Lecture 7

L7-Higher Logical Accuracy

Video
00:21:40

Lecture 8

L8-Control Prompting

Video
00:20:17

Lecture 9

L9-Persona driven Prompting

Video
00:24:27

Lecture 10

L10-Task Decompisition in AI

Video
00:24:06

Lecture 11

L11-Ethical LLM Control Techiniques

Video
00:16:05

Lecture 12

L12-LLM Manipulation Techiniques

Video
00:48:49

Lecture 13

L13-Layering Workflows

Video
00:40:33

Lecture 14

L14-Dynamic AI State Management

Video
00:16:50

Lecture 15

L15-Hidden AI Representation Control

Video
00:31:36

Course Instructor