Master Python fundamentals, from setup to OOP, with practical projects, enabling proficiency in data manipulation, model deployment, and core AI/ML concepts. 

Topics Covered 

• Why is Python Programming Emergent?  

• Installing & Setting up Python on System  

• What are Variables & Uses of Variables?  

• Python Revisit: Keywords, Data Types, Operators  

• Decision Making  

• Looping  

• User Defined Function  

• Lambda Function  

• Error Handling in Python  

• Python Generators  

• Python Modules: Usage and Installation  

• Understanding the OOP of Python  

• Project on Python 

Skills Acquired 

• Python Proficiency  

• Problem-solving  

• Data Visualization  

• AI/ML Concepts 

• Model Deployment 

A foundational module for PG Diploma in Al and ML certification courses covering key statistical concepts and techniques essential for data analysis and machine learning applications. 

Topics covered 

• Virtual Lab Setup (Kali Linux, Windows, Metasploitable) | Demo   

• Introduction to Kali Linux Environment   

• Linux File System | Demo   

• Basic Linux Commands | Demo   

• Configuring a Secure Lab Environment 

Skills Acquired 

• Probability Theory  

• Data Distributions  

• Statistical Inference  

• Data Distributions  

• Hypothesis Testing 

Learn how to draw conclusions from data using inferential statistics. Understand hypothesis testing, confidence intervals, and apply statistical tests like Z-test and Chi-square. 

Topics Covered 

• What are Inferential Statistics?  

• Null Hypothesis  

• Alternative Hypothesis  

• Confidence Interval  

• Significance Value  

• Real Industry Program of Inferential Statistics  

• Hypothesis Problem  

• Z – test with Proportion Problem  

• Chi Square Test  

Skills Acquired 

• Hypothesis Testing  

• Statistical Inference  

• Z-test  

• Chi-square test  

• Confidence Interval calculations 

Learn how to draw conclusions from data using inferential statistics. Understand hypothesis testing, confidence intervals, and apply statistical tests like Z-test and Chi-square. 

Topics Covered 

• What are Inferential Statistics?  

• Null Hypothesis  

• Alternative Hypothesis  

• Confidence Interval  

• Significance Value  

• Real Industry Program of Inferential Statistics  

• Hypothesis Problem  

• Z – test with Proportion Problem  

• Chi Square Test  

Skills Acquired 

• Hypothesis Testing  

• Statistical Inference  

• Z-test  

• Chi-square test  

• Confidence Interval calculations 

Master NumPy arrays for efficient data manipulation. Learn array creation, manipulation, data types, and perform arithmetic and statistical operations. 

Topics Covered 

• Python NumPy Array  

• Creating Accessing, Manipulating NumPy Array  

• NumPy Data Types  

• Array Attributes  

• Data Operations  

• Arithmetic and Statistical Methods  

• Sort, Search, and Count  

• Practical 

Skills Acquired 

• NumPy Array Manipulation  

• Data Operations  

• Statistical Methods   

• Array Attributes  

• Data Sorting and Searching 

Gain expertise in Pandas Series and Data Frames for data analysis. Learn data manipulation, file handling, grouping, and handling missing data. 

Topics Covered 

• The Series and Data Frame  

• Creating, Accessing, Manipulating Pandas Data  

• Series and Data Frame Attributes & Basic Functions  

• Excel Automation with OpenPyXL  

• Statistical Functions; String Functions  

• Logical Indexing; Sorting & Reindexing  

• Merging, Joining & Concatenation of Data  

• Pandas File Handling  

• Grouping Data  

• Function Application  

• Missing Data & Treatment  

• Practical  

Skills Acquired 

• Pandas Data Manipulation  

• Data Analysis   

• File Handling  

• Data Grouping  

• Missing Data Treatment 

Learn to connect Python to MySQL databases. Execute SQL queries, handle transactions, and retrieve data into Pandas Data Frames for further analysis. 

Topics Covered 

• Installing and configuring MySQL Connector   

• Connecting to a MySQL database from Python  

• Executing SELECT, INSERT, UPDATE, DELETE queries Handling transactions.  

• Retrieving data from MySQL into Pandas data frames, performing data manipulations using Python.  

Skills Acquired 

• MySQL Database Interaction  

• SQL Query Execution  

• Data Retrieval  

• Transaction Handling  

• Python-MySQL Integration 

Build integrated data dashboards using Python, Excel, and MySQL. Learn code optimization techniques and implement robust error handling. 

Topics Covered 

• Integrating Python, Excel, and MySQL to create a data dashboard  

• Using visualization libraries (Matplotlib, Seaborn)  

• Connecting the application to MySQL for data storage  

• Techniques for optimizing Python and SQL code  

• Implementing robust error handling in Python and SQL  

• Work on a comprehensive project integrating Python, Excel, and MySQL  

• Evaluation Of a Model  

• Practical  

Skills Acquired 

• Data Dashboard Development  

• Code Optimization  

• Error Handling  

• Data Visualization  

• Database Integration 

Explore unsupervised learning with a focus on clustering theory and K-means clustering. Learn to identify patterns in unlabeled data. 

Topics Covered 

• Clustering Theory  

• K-means Clustering  

• Practical  

Skills Acquired 

• Clustering Theory  

• K-means Clustering  

• Unsupervised Learning Techniques  

• Pattern Recognition. 

Apply acquired AI/ML skills to a real-world problem, demonstrating end-to-end project execution, from data analysis to model deployment and evaluation. 

Topics Covered 

• Project Conceptualization and Problem Definition  

• Data Acquisition and Preprocessing  

• Model Selection and Development  

• Model Training and Optimization  

• Deployment Strategies and Implementation  

• Performance Evaluation and Reporting  

• Team Collaboration and Project Management  

• Presentation of Project Findings  

Skills Acquired 

• End-to-End AI/ML Project Execution  

• Real-world Problem Solving  

• Model Deployment and Evaluation  

• Project Management and Collaboration  

• Effective Communication of Technical Findings