

Sahil's profile, diploma and contact details have been verified by our experts
Sahil
- Rate 332 GHS
- Response 1h
-
Students3
Number of students Sahil has accompanied since arriving at Superprof
Number of students Sahil has accompanied since arriving at Superprof

332 GHS/hr
Unfortunately, this tutor is unavailable
- Maths
- Statistics
- Algorithms
Data Scientist and Machine Learning Engineer, Master in Data Science - UOA, Software Engineering background. Specialise in teaching Data Science, Machine Learning, Programming, Computer Science, Maths
- Maths
- Statistics
- Algorithms
Lesson location
About Sahil
Meet Sahil Bahl, a seasoned data scientist with years of experience in the field and a passion for teaching. Sahil has a proven track record of success in data science and machine learning, having worked on a variety of projects for companies in a range of industries. Sahil holds a Master's degree in Data Science from the University of Auckland with First Class Honours and a First in Class Award in Advanced Machine Learning.
Whether you are a beginner just starting out or an advanced student looking to deepen your understanding, Sahil has the expertise to help you reach your goals. He will work with you to assess your strengths and weaknesses and tailor his lessons to meet your individual needs and learning style.
About the lesson
- Primary school
- Junior high school
- SHS 1
- +8
levels :
Primary school
Junior high school
SHS 1
SHS 2
SHS 3
Adult Education
Facultate (Licență)
Master's degree
Higher national diploma
Doctor of philosophy
Other
- English
All languages in which the lesson is available :
English
Attention all students who want to excel in the exciting and in-demand fields of programming, computer science, data science and machine learning! Are you looking for a teacher who can help you reach your full potential in these subjects? Look no further!
I am a seasoned data scientist, machine learning professional and educator, with years of experience in programming, computer science, and machine learning. I have a passion for teaching and am dedicated to helping students develop the skills and knowledge they need to succeed in these rapidly-evolving fields.
Whether you are just starting out or looking to take your skills to the next level, I have the expertise to help you reach your goals. My lessons are personalized, interactive, and hands-on, designed to challenge you and help you develop the practical skills you need to succeed.
In my lessons, you will learn the core concepts and principles of programming, computer science, and machine learning, as well as how to apply these concepts in real-world projects. You will have the opportunity to work on cutting-edge projects, using the latest tools and technologies, and to receive regular feedback and guidance from me to help you improve your skills and knowledge.
A comprehensive data science teaching plan could include the following topics and activities:
Introduction to Data Science: Overview of data science, its importance and applications in various industries, and the skills and tools required to become a data scientist.
Data Wrangling: Techniques for cleaning, transforming, and merging data from different sources, using tools such as Python's Pandas library.
Exploratory Data Analysis: Techniques for visualizing and summarizing data, including histograms, scatter plots, and box plots, to gain insights into the data.
Data Visualization: Using libraries such as Matplotlib and Seaborn to create compelling and informative visualizations to communicate data insights.
Statistics: An introduction to descriptive and inferential statistics, including hypothesis testing, confidence intervals, and regression analysis.
Machine Learning: An introduction to the fundamental concepts of machine learning, including supervised and unsupervised learning, and popular algorithms such as linear regression, k-nearest neighbors, and decision trees.
Deep Learning: An overview of deep learning techniques, including artificial neural networks and Convolutional Neural Networks, and how they can be used to solve complex problems.
Project-based learning: Students will work on real-world projects, such as building predictive models, creating data visualizations, or analyzing a large dataset, to apply the concepts and skills learned in class.
Career Development: An overview of the various career paths in data science, including data analyst, data engineer, and data scientist, and the skills and experience required for each role.
In addition to these topics, the teaching plan should also include regular assessments, quizzes, and exams to assess student learning, as well as opportunities for students to ask questions, receive feedback, and participate in class discussions.
Rates
Rate
- 332 GHS
Pack prices
- 5h: 1660 GHS
- 10h: 3320 GHS
online
- GHS332/h
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