Hritik - Maths teacher - Birmingham
1st lesson free
Hritik - Maths teacher - Birmingham

Hritik's profile and their contact details have been verified by our experts

Hritik

  • Rate $28
  • Response 10h
  • Students

    Number of students Hritik has taught since their arrival at Superprof

    3

    Number of students Hritik has taught since their arrival at Superprof

Hritik - Maths teacher - Birmingham

$28/h

1st lesson free

Contact

1st lesson free

1st lesson free

  • Maths
  • Statistics
  • Science
  • Algorithms
  • Computing

Artificial Intelligence and Machine Learning Graduate from the University of Birmingham | Ex-Samsung Data Scientist | I love to teach

  • Maths
  • Statistics
  • Science
  • Algorithms
  • Computing

Lesson location

About Hritik

From Math & Statistics --> Coding --> Data Science

Learn and apply Math with logic building

Mathematics & Statistics:

Calculus: Limits, derivatives, and integrals.
Linear Algebra: Vectors, matrices, eigenvalues, eigenvectors.
Probability: Probability distributions, random variables, expected values.
Statistics: Descriptive statistics, inferential statistics, hypothesis testing.
Multivariate Calculus: Gradients, partial derivatives.
Optimization: Gradient descent, optimization techniques.

Coding:
Programming Languages: Choose a language such as Python or R.
Basic Programming Concepts: Variables, data types, loops, conditionals.
Data Structures: Lists, arrays, dictionaries, sets.
Functions and Modules: Writing functions, modular programming.
Version Control: Git and GitHub.
Command Line: Basic command-line operations.

Data Science:
Python Libraries: NumPy, Pandas, Matplotlib, Seaborn.
Data Cleaning: Handling missing data, outliers.
Data Visualization: Creating effective visualizations.
Statistical Modeling: Regression analysis, hypothesis testing.
Machine Learning: Supervised and unsupervised learning algorithms.
Feature Engineering: Creating relevant features from raw data.
Model Evaluation: Metrics for evaluating model performance.
Data Preprocessing: Scaling, normalization, encoding.
Big Data Technologies: Apache Spark, Hadoop.
Deep Learning (Optional): Neural networks, TensorFlow, PyTorch.
Natural Language Processing (NLP): Text mining, sentiment analysis.
Time Series Analysis: Handling time-dependent data.
Databases: SQL, working with databases.
Cloud Platforms: AWS, Azure, Google Cloud.
Communication and Presentation: Explaining findings to non-technical stakeholders.

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About the lesson

  • Primary
  • Secondary
  • Tertiary
  • +5
  • levels :

    Primary

    Secondary

    Tertiary

    Tvet

    Adult Education

    University

    Masters

    Doctorate

  • English

All languages in which the lesson is available :

English

From High School Statistics to Engineering Maths to Data Science

Learn Math and Statistics visually with logic breakdown

Qualifications: MSc Artificial Intelligence and Machine Learning | University of Birmingham | 2:1 Merit

Who are my audience: Anyone having basic idea about math and statistics

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Rates

Rate

  • $28

Pack rates

  • 5h: $141
  • 10h: $283

online

  • $28/h

Travel

  • + $$15

free lessons

This first lesson offered with Hritik will allow you to get to know each other and clearly specify your needs for your next lessons.

  • 1hr

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