I conduct this course online for Hodmas University College (HUC) Students in Summer Semester.

Course Plan

• Lecture – 01: Introduction to Data Analysis.

• Lecture – 02: Introduction to Python.

• Practice Session – 01: Problem-solving with python.

• Lecture – 03: Introduction to Python Libraries. Hands-on in Numpy.

• Lecture – 04: Introduction to Pandas.

• Practice Session – 02: Assignment on Numpy and Pandas.

• Lecture – 05: Reading and writing data with Pandas & brief discussion on SciPy.

• Lecture – 06: Data Visualization using Matplotlib and Seaborn.

• Practice Session – 03: Data set reading, analyzing, manipulating, and visualizing assignment.

• Lecture – 07: Introduction to Machine Learning using Python.

• Lecture – 08: Machine Learning Algorithms using Python.

• Practice Session – 04: Assignment on Machine Learning problem.

• Lecture – 09: Introduction to Artificial Intelligence using python.

• Lecture – 10: Single and Multi-layer Perceptron using TensorFlow.

• Practice Session – 05: Assignment on SLP or MLP.

• Lecture – 11: An Example of Meteorological Data

• Lecture – 12: Embedding the Javascript D3 library in the Ipython Notebook.

• Practice Session – 06: Assignment on Meteorological Data.

• Lecture – 13: Recognizing Handwritten digits using machine learning and Deep Learning.

• Lecture – 14: Textual Data Analysis with NLTK.

• Practice Session – 07: Assignment on NLTK or Handwritten Digit Recognition.

• Lecture – 15: Image Analysis with OpenCV.

• Lecture – 16: Data Analyst market analysis and overall discussion on the course.

• Practice Session – 08: Assignment on Image analysis.

I am offering this course online to HUC students in Fall Semester.

Course Plan:

Introduction

- Communication Systems

- Data Networks

Data and Signals Analog and Digital

- Periodic and Aperiodic Analog Signals

- Digital Signals

- Transmission Impairments

- Data Rate Limits

- Performance of Transmission System

QUIZ I

Digital Transmission

- Digital to Digital Conversion

- Analog to Digital Conversion

- Transmission Modes

Analog Transmission

- Digital to Analog Conversion

- Analog to Analog Conversion

QUIZ II

Bandwidth Utilization

- Multiplexing

- Spread Spectrum

Transmission Media

- Guided and Unguided Media

Error Detection and Correction

- Types of Errors, redundancy, detection vs correction

- Types of Coding – Hamming Codes, Cyclic Redundancy Check, Checksum

FINAL

Grading: Quiz I = 20%, Quiz II = 30%, Final = 50% (all quizes/exams are open book and cumulative)

I am offering this course online to HUC students in Fall Semester.

Course Plan:

Week 1: Introduction
- C Programming Recap
- Basic Data Structures including array, string, structure, union.

Week 2: Analysis of Algorithms, Searching and Sorting Algorithms
- Analyzing complexities of Algorithms
- Searching Algorithms
- Sorting Algorithms

Week 3: Dynamic Data Structures
- Pointer and Linked List
- Stack
- Queue
- Heap
- Hashing

Week 4: Graph Data Structures
- Graph and its representation
- Common Graph Traversal Problems, i.e. BFS and DFS

MID-TERM

Week 5: Graph Algorithms
- Digraphs, weighted graphs: representations, applications
- Reachability: Warshall
- Minimum Spanning Tree (MST): Prim's and Kruskal's
- Shortest path problems: Dijkstra (single source SPP) and Floyd (all-pair SSP)

Week 6: Search Tree Data Structures
- Binary Tree
- Binary Search Tree
- B and B+ Tree
- AVL Tree

Week 7: Search Tree Algorithms
- Tree traversal
- Basic BST operation: insertion, join, deletion, rotation
- Self-adjusting trees (AVL)

Week 8: String Algorithms and Randomized Algorithms
- Pattern matching: Boyer-Moore, Knuth-Morris-Pratt
- Tries
- Text compression: Huffman code

FINAL

Grading: Mid Semester = 20%, Final = 30%, Weekly Assignments = 20%, Large Assignment = 20%, Attendance = 10% (all quizes/exams are open book and cumulative)

I conducted this course to grade 11-12 students at Rajshahi Cantonment Public School and College