- Data Analytics with Python
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.
2. Data Communication and Networking
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)
3. Data Structure and Algorithm
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)
4. Information and Communication Technology
I conducted this course to grade 11-12 students at Rajshahi Cantonment Public School and College