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Data Science Interview Challenge
course content

Course Content

Data Science Interview Challenge

Data Science Interview Challenge

1. Python

IntroductionChallenge 1: List ComprehensionChallenge 2: String ManipulationChallenge 3: Dictionary ManipulationChallenge 4: Nested LoopsChallenge 5: ClassesTheoretical Questions

2. NumPy

Challenge 1: Array CreationChallenge 2: Array ManipulationChallenge 3: Statistical InsightsChallenge 4: Handling Missing ValuesChallenge 5: Subarray SortingTheoretical Questions

3. Pandas

Challenge 1: DataFrame CreationChallenge 2: Data GroupingChallenge 3: Indexing and MultiIndexingChallenge 4: Altering DataFrameChallenge 5: Iterating Over DataTheoretical Questions

4. Matplotlib

Challenge 1: Fundamentals of PlottingChallenge 2: Other Graph TypesChallenge 3: SubplotsChallenge 4: Customizing PlotsChallenge 5: Adding Text to PlotsTheoretical Questions

5. Seaborn

Challenge 1: Visualizing DistributionsChallenge 2: Exploring Categorical DataChallenge 3: Relational PlotsChallenge 4: Regression PlotsChallenge 5: Matrix PlotsTheoretical Questions

6. Statistics

Challenge 1: Probabilities and DistributionsChallenge 2: Bayes' TheoremChallenge 3: Hypothesis TestingChallenge 4: Confidence IntervalsChallenge 5: CorrelationTheoretical Questions

7. Scikit-learn

Challenge 1: Data ScalingChallenge 2: Basic Model CreationChallenge 3: PipelinesChallenge 4: Cross-validationChallenge 5: Hyperparameter TuningTheoretical Questions

Challenge 4: Nested Loops

Nested loops in Python are a cornerstone for advanced iteration over data sets. Their importance lies in:

  • Multi-dimensional Data Handling: They allow for iterating over complex data structures like matrices or multi-dimensional lists, enabling deep data traversal.
  • Combination and Permutation: Nested loops are the go-to solution when you need to evaluate all possible combinations or permutations of multiple lists.
  • Granular Control: They offer fine-tuned control over iteration, allowing programmers to dictate the exact flow and conditions of looping.

Using nested loops, developers can harness the power of iteration to its fullest potential.

Task

The goal is to generate a matrix (a list of lists) where the outer list contains n lists and each inner list contains m integers. These integers should be in ascending order starting from 1.

Nested Loops
  1. Set up for loop.
  2. Set up while loop.
  3. Append inner row.
  4. Increase counter.
  5. Increase row index.
  6. Append matrix.

Task

The goal is to generate a matrix (a list of lists) where the outer list contains n lists and each inner list contains m integers. These integers should be in ascending order starting from 1.

Nested Loops
  1. Set up for loop.
  2. Set up while loop.
  3. Append inner row.
  4. Increase counter.
  5. Increase row index.
  6. Append matrix.

Everything was clear?

Section 1. Chapter 5
toggle bottom row

Challenge 4: Nested Loops

Nested loops in Python are a cornerstone for advanced iteration over data sets. Their importance lies in:

  • Multi-dimensional Data Handling: They allow for iterating over complex data structures like matrices or multi-dimensional lists, enabling deep data traversal.
  • Combination and Permutation: Nested loops are the go-to solution when you need to evaluate all possible combinations or permutations of multiple lists.
  • Granular Control: They offer fine-tuned control over iteration, allowing programmers to dictate the exact flow and conditions of looping.

Using nested loops, developers can harness the power of iteration to its fullest potential.

Task

The goal is to generate a matrix (a list of lists) where the outer list contains n lists and each inner list contains m integers. These integers should be in ascending order starting from 1.

Nested Loops
  1. Set up for loop.
  2. Set up while loop.
  3. Append inner row.
  4. Increase counter.
  5. Increase row index.
  6. Append matrix.

Task

The goal is to generate a matrix (a list of lists) where the outer list contains n lists and each inner list contains m integers. These integers should be in ascending order starting from 1.

Nested Loops
  1. Set up for loop.
  2. Set up while loop.
  3. Append inner row.
  4. Increase counter.
  5. Increase row index.
  6. Append matrix.

Everything was clear?

Section 1. Chapter 5
toggle bottom row

Challenge 4: Nested Loops

Nested loops in Python are a cornerstone for advanced iteration over data sets. Their importance lies in:

  • Multi-dimensional Data Handling: They allow for iterating over complex data structures like matrices or multi-dimensional lists, enabling deep data traversal.
  • Combination and Permutation: Nested loops are the go-to solution when you need to evaluate all possible combinations or permutations of multiple lists.
  • Granular Control: They offer fine-tuned control over iteration, allowing programmers to dictate the exact flow and conditions of looping.

Using nested loops, developers can harness the power of iteration to its fullest potential.

Task

The goal is to generate a matrix (a list of lists) where the outer list contains n lists and each inner list contains m integers. These integers should be in ascending order starting from 1.

Nested Loops
  1. Set up for loop.
  2. Set up while loop.
  3. Append inner row.
  4. Increase counter.
  5. Increase row index.
  6. Append matrix.

Task

The goal is to generate a matrix (a list of lists) where the outer list contains n lists and each inner list contains m integers. These integers should be in ascending order starting from 1.

Nested Loops
  1. Set up for loop.
  2. Set up while loop.
  3. Append inner row.
  4. Increase counter.
  5. Increase row index.
  6. Append matrix.

Everything was clear?

Nested loops in Python are a cornerstone for advanced iteration over data sets. Their importance lies in:

  • Multi-dimensional Data Handling: They allow for iterating over complex data structures like matrices or multi-dimensional lists, enabling deep data traversal.
  • Combination and Permutation: Nested loops are the go-to solution when you need to evaluate all possible combinations or permutations of multiple lists.
  • Granular Control: They offer fine-tuned control over iteration, allowing programmers to dictate the exact flow and conditions of looping.

Using nested loops, developers can harness the power of iteration to its fullest potential.

Task

The goal is to generate a matrix (a list of lists) where the outer list contains n lists and each inner list contains m integers. These integers should be in ascending order starting from 1.

Nested Loops
  1. Set up for loop.
  2. Set up while loop.
  3. Append inner row.
  4. Increase counter.
  5. Increase row index.
  6. Append matrix.

Section 1. Chapter 5
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