Course Description
- Comprehensive training in analytics, machine learning, and AI.
- Designed for beginners and professionals seeking practical knowledge.
- Hands-on projects with real-world datasets.
Who Can Take This Course?
- Beginners interested in Data Science.
- IT professionals expanding their expertise.
- Business analysts aiming for data-driven decision-making.
- Students from engineering, statistics, or computer science.
- Entrepreneurs seeking data insights for business growth.
Job Opportunities
- Data Scientist
- Machine Learning Engineer
- Data Analyst
- AI Specialist
- Business Intelligence Developer
- Big Data Engineer
Course Curriculum
BOOT CAMP 1 – THE COMPLETE PYTHON PROGRAMMING
CHAPTER 1 – INTRODUCTION TO PYTHON PROGRAMMING
CHAPTER 2 – VARIABLES AND EXPRESSIONS
CHAPTER 3 – INTRODUCTION TO DATA TYPES IN PYTHON
CHAPTER 4 – FLOW CONTROL STATEMENTS – CONDITIONAL STATEMENTS
CHAPTER 5 – FLOW CONTROL STATEMENTS – LOOPING STATEMENTS & TRANSFER STATEMENTS
CHAPTER 6 – FUNCTIONS IN PYTHON
CHAPTER 7 – FUNCTIONS ADVANCED IN PYTHON
CHAPTER 8 – EXPLORING STRING DATATYPE
CHAPTER 9 – EXPLORING LISTS AND DICTIONARIES
CHAPTER 10 – OBJECT ORIENTED PROGRAMMING IN PYTHON
CHAPTER 11 – MODULES IN PYTHON
CHAPTER 12 – FILE HANDLING IN PYTHON
CHAPTER 13 – EXCEPTION HANDLING IN PYTHON
BOOT CAMP 2 – DATA ANALYTICS WITH PYTHON
CHAPTER 1 – COMPUTATIONAL MATHEMATICS IN NUMPY
CHAPTER 2 – DATA TRANSFORMATIONS WITH PANDAS
CHAPTER 3– DATA CLEANING AND PREPARATIONS
CHAPTER 4 – DATA WRANGLING
CHAPTER 5 – DATA AGGREGATIONS
CHAPTER 6 – DESCRIPTIVE ANALYTICS (STATISTICS)
CHAPTER 7 – DATA VISUALIZATIONS BY MATPLOTLIB, SEABORN
BOOT CAMP 3 – SQL FOR DATA ANALYTICS
CHAPTER 1 – INTRODUCTION TO DATABASE
CHAPTER 2 – INTRODUCTION TO RELATIONAL DATABASE
CHAPTER 3 – INTRODUCTION TO SQL
CHAPTER 4 – SELECT AND WHERE CLAUSES
CHAPTER 5 – OPERATORS IN SQL
CHAPTER 6 – JOIN OPERATIONS
CHAPTER 7 – GROUP BY OPERATIONS
BOOT CAMP 4 – ADVANCED EXCEL FOR DATA ANALYTICS
CHAPTER 1 – BASIC FUNCTIONS IN EXCEL
CHAPTER 2 – ADVANCED FUNCTIONS IN EXCEL
CHAPTER 3 – VLOOKUP IN EXCEL
CHAPTER 4 – FILTERS AND ADVANCED FILTERS
CHAPTER 5 – BASIC TABLE AND ADVANCED TABLE
CHAPTER 6 – PIVOT TABLES IN EXCEL
CHAPTER 7 – CONDITIONAL FORMATTING IN EXCEL
CHAPTER 8 – DATA VALIDATION IN EXCEL
CHAPTER 9 – POWER QUERY IN EXCEL – SECTION1
CHAPTER 10 – POWER QUERY IN EXCEL – SECTION2
CHAPTER 11 – POWER QUERY IN EXCEL – SECTION3
BOOT CAMP 5 – DATA VISUALIZATION BY MICROSOFT POWERBI
CHAPTER 1 – BASIC CHARTS AND MAPS IN POWERBI
CHAPTER 2 – TABLES AND MATRIX IN POWERBI
CHAPTER 3 – M FUNCTIONS IN POWERBI
CHAPTER 4 – OTHER CHARTS IN POWERBI
CHAPTER 5 – ADVANCED CHARTS IN POWERBI
CHAPTER 6 – POWER QUERIES IN POWERBI
CHAPTER 7 – DATA TRANSFORMATION IN POWERBI
CHAPTER 8 – DASHBOARD CREATION AND PUBLISH ON POWERBI SERVICE
CHAPTER 9 – AI FEATURES IN POWERBI
CHAPTER 10 – POWER BI DASHBOARD END TO END PROJECT
BOOT CAMP 6 – PREDICTIVE ANALYTICS
CHAPTER 1 – INTRODUCTION TO MACHINE LEARNING
CHAPTER 2 – SUPERVISED LEARNING ML ALGORITHM 1
CHAPTER 3 – SUPERVISED LEARNING ML ALGORITHM 2
CHAPTER 4 – SUPERVISED LEARNING ML ALGORITHM 3
CHAPTER 5 – SUPERVISED LEARNING ML ALGORITHM 4
CHAPTER 6 – SUPERVISED LEARNING ML ALGORITHM 5
CHAPTER 7 – SUPERVISED LEARNING ML ALGORITHM 6
CHAPTER 8 – SUPERVISED LEARNING ML ALGORITHM 7
CHAPTER 9 – UNSUPERVISED LEARNING ML ALGORITHM 1
CHAPTER 10– CAPSTONE PROJECT 1
BOOT CAMP 7: CHATGPT FOR PYTHON
CHAPTER 1: INTRODUCTION TO PYTHON, PYCHARM, AND PROMPTING WITH CHATGPT
CHAPTER 2: MORE CONTROL FLOW, COLLECTIONS, AND COMPREHENSION
CHAPTER 3: INHERITANCE AND OBJECT-ORIENTED PROGRAMMING
CHAPTER 4: IMPROVING CODE AND READABILITY WITH CHATGPT
CHAPTER 5: TYPES OF PROMPTS AND IMPORTANT KEYWORDS