MathClubforKids

  • 4500 Stonecrest Dr, Ellicott City, MD 21043, USA

Statistics with Data science using Python

WEEK 1 : Introduction

  1. Basic Introduction to Data Science.
  2. Data Science Impacts and Importance.
  3. Why Mathematics and Statistics is important?
  4. Real-life application.
  5. Introduction to Google Colab.
  6. Python syntax and data types.
  7. Basic arithmetic and algebraic operation.
  8. Basic codes using Python (Print your name, sum, difference, etc)
  9. Python keywords.

Week 2 : Understanding Data

  1. What is Data?
  2. Qualitative vs Quantitive data.
  3. Primary and Secondary data with real-life examples.
  4. Data representation using statistical tools.
  5. Discrete vs Continuous data.
  6. Bar chart, histogram, line diagram, pie-chart.
  7. Concept of measure of Central tendency.
  8. Difference between Arithmetic Mean, Geometric Mean, and Harmonic Mean.
  9. Impact of Median in our real life.
  10. Calculate Mode.

Week 3: Python Code

  1. If- else condition in Python.
  2. Python code using condition.
  3. Python Loops and types of loops.
  4. Basic Mathematical code using for loop.
  5. Pattern code using for loop.
  6. Basic Mathematical code using While loop.
  7. Break and Continue statement in Python.
  8. Assignments.

Week 4: Statistics with Python

  1. Measure of Dispersion.
  2. How do you calculate the range of any dataset?
  3. Why do we calculate various types of deviation?
  4. Calculate Standard and Mean Deviation.
  5. Import NumPy Libraries.
  6. Calculate basic calculations of Statistics using NumPy.
  7. Assignments

Week 5: NumPy library

  1. Create a Matrix.
  2. Array Creation.
  3. Array Operation.
  4. Indexing and Slicing.
  5. Shape Manipulation.
  6. Mathematical Function.
  7. Statistical Function. Assignment.

Week 6: Basic of Probability

  1. Introduction to Probability.
  2. Coin Problems.
  3. Dice Problems.
  4. Cards Problems.
  5. Concepts of Basic set theory.
  6. Venn Diagram, Union, and Intersection.
  7. Python Program to solve probability problems.
  8. Assignments.

Week 7: Arithmetic and Algebra

  1. Distance, time, and speed problem using Python.
  2. Ratio and proportion real-life problem solving using Python.
  3. Percentage calculation
  4. Simple and Compound Interest.
  5. Basic Mensuration problem using Python.
  6. Basic Trigonometry.
  7. Application of Trigonometry using Python. Assignments

Week 8: Pandas Library

  1. Introduction to Pandas Library.
  2. How to create a data frame and its importance.
  3. How to read data from CSV OR JSON files.
  4. Data cleaning using Pandas.
  5. Clean wrong format, wrong data, Duplicate values.
  6. Data Manipulation.
  7. Group-By function, Merging, and joining. Assignments.

Week 9: Data Visualization

  1. Introduction to Matplotlib Libraries.
  2. Pyplot in Matplotlib.
  3. Scatter plot.
  4. Bar Chart and Histogram using Python.
  5. Pie-chart using Python.
  6. 3D plots.
  7. Work with real-life data.
  8. Assignments.

Week 10: Machine Learning

  1. Data cleaning.
  2. Supervised vs Unsupervised Learning.
  3. Introduction to Scikit-Learn library.
  4. Concepts of correlation.
  5. Concepts of linear regression.
  6. Use Linear Regression using Python.
  7. Advantages and Disadvantages of linear regression.
  8. Concepts of Multiple Regression, Logistic Regression.
  9. Projects.

Week 11: Deep Learning

  1. Classification and Clustering
  2. Real-life examples of different machine learning algorithms.
  3. Concept of AI.
  4. How to use ChatGPT.
  5. Concepts of Deep Learning.
  6. Importance of Neural Network.
  7. Image recognition using deep learning.
  8. Introduction to NLP. Projects.

Week 12: Project with QNA

  1. Project discussion.
  2. QNA Season.
  3. MCQ test for mathematics & Statistics.
  4. Coding test for Python.

US / Dubai / Singapore Price

$100 / month

  • Course Duration : 12 weeks/ 3 months
Your Python/Math/Olympiad/Data Course

INDIA PRICE
(For residents of India Only)

₹6000

  • Course Duration : 12 weeks/ 3 month

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Experts

Sourish Sarkar

Master of Science in QMS
Indian Statistical Institute Statistical Quality Control , Operation Research