medini bv
Collaborative Computer Science & coding lessons with creativity
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medini bv
Bachelors degree
Enroll after the free trial
Each lesson is 55 min
50 lessons
20% off
/ lesson
30 lessons
15% off
/ lesson
20 lessons
10% off
/ lesson
10 lessons
5% off
/ lesson
5 lessons
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/ lesson
1 lessons
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/ lesson
medini - Know your tutor
Hello, I'm Medini BV, a Computer Science and Robotic Engineer and tutor with a Bachelors in Electronics and Masters in Robotics. Am Having 3+ years of Industrial experience and 2+ years of tutoring. In this journey i have poured knowledge to 200+ students including working professional, Engineering, College and School students. My teaching philosophy revolves around making complex concepts simple for students and give depth knowledge with practical implementation. I specialize in teaching Python, Artificial Intelligence, Machine Learning. Deep Learning, Computer Vision, Data Science, C, C++, Embedded Systems, Electronics, Arduino programming, ROS and STEM for kids. I believe in engaging students through interactive learning methods to ensure they grasp the subject thoroughly. Let's embark on a learning journey together!
medini graduated from GOVERNMENT ENGINEERING COLLEGE RAMANAGARA
Programming tutor specialities
Paired coding
Exam prep
Job readiness
Upskilling
Test prep
Assignment help
Next Generation Science Standards - NGSS (USA)
Project help
Debugging
Learner for programming class
All Levels
Adult / Professional
College
School
Programming class overview
As a Computer Science and Programming tutor, I believe in making learning engaging and collaborative. I personalize classes based on students' interests, level of understanidng making the session more interactive. My teaching style is empathetic and practical, focusing on real-world applications of concepts. I also incorporate creative methods to enhance learning, such as gamified activities. I create a structured plan with exercises to help students build their skills gradually. I aim not only to help them academically but also to prepare them for internships and jobs in leading tech companies giving them industrial exposure and requirements.
Your programming tutor also teaches
Computer Science
Matlab
Python
Artificial Intelligence
C
C++
Computer Science concepts taught by medini
The session focused on data preprocessing techniques in Python, including column selection, data transformation using encoding methods, scaling, normalization, and data grouping. The Student practiced implementing these techniques using Pandas and Scikit-learn on a sample dataset. The next steps involve further data transformation, visualization, and potentially implementing machine learning models.
Data Transformation: Encoding Categorical Variables
Data Transformation: Scaling and Normalization
Data Analysis: Grouping and Aggregation
Feature Selection: Dropping Irrelevant Columns
The student and tutor discussed data analysis and engineering using Python, focusing on data cleaning techniques. The student learned to use Pandas and other libraries to handle missing data, remove duplicates, and correct data types in preparation for analysis and machine learning. The next steps include categorical cleansing and statistical analysis.
Data Pipelining in Data Analysis/Engineering
Exploratory Data Analysis (EDA) Tools
Python Libraries for Data Analysis
Data Cleaning and Preprocessing
Data Transformation
Descriptive Statistics and Data Understanding
The session involved debugging line sensor and encoder code for a robot. The student worked on resolving errors in the encoder code and troubleshooting issues with sensor readings. The tutor provided guidance and code modifications to achieve functional sensor readings. The next step is to integrate the sensor code with the motor control code for robot movement, planned for the next session.
Identifying and Resolving Code Errors
Analog vs. Digital Readings
Library Integration and Troubleshooting
Hardware Connections and Pin Assignments
Understanding Sensor Calibration
The Student and Tutor worked on debugging the Student's line-following robot code by adjusting sensor pin configurations and integrating the code with the robot's hardware. They tested and modified code related to line sensor readings, motor control, and calibration routines to improve the robot's performance. The tutor will rewrite the code and share it for testing in the next session, focusing on assessment file requirements.
Line Sensor Pin Configuration
Library Integration and Management
Calibration Process for Line Sensors
Debugging Strategy: Step-by-Step Approach
Motor Speed Configuration
The Student and Tutor discussed Python modules, packages, and libraries, focusing on installing external libraries with pip. The session covered pandas Series and DataFrames, demonstrating their creation and basic indexing. The Student began working on reading an Excel file into pandas and will continue practicing indexing and column name manipulation for homework.
Exploring Data: .head() and .tail()
Reading Data with Pandas
Indexing with .loc and .iloc
Pandas: Series vs. DataFrame
PIP - Python Package Index
Modules
Libraries
and Packages
The Student reviewed voltage divider circuits and derived expressions for output voltage, including scenarios with variable resistance. They worked through problems involving sensitivity analysis and flex sensors, designing a circuit and deriving a formula for flex angle. The Student was assigned to complete the remaining questions as homework and email them for review.
Voltage Divider Circuit Analysis
Resistance Perturbation & Linear Approximation
Sensitivity Analysis
Flex Sensor Application
Teaching tools used by tutor
Jupyter Notebook
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