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Data Analytics Engineering: Probability & Techniques

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Data Analytics Engineering: Probability & Techniques

Instructor: Sri Radhakrishnan

Included with

Learn more

4 modules

Gain insight into a topic and learn the fundamentals.

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Prepare for a degree

Learn more

4 modules

Gain insight into a topic and learn the fundamentals.

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Prepare for a degree

Learn more

Skills you'll gain

Tools you'll learn

Pandas (Python Package)

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 assignments

Taught in English

91% of learners achieved a positive career outcome

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There are 4 modules in this course

This course offers students an opportunity to learn fundamentals of computation required to understand and analyze real world data. The course helps students to work with modern data structures, apply data cleaning and data wrangling operations. The course covers conceptual and practical applications of probability and distribution, cluster analysis, text analysis and time series analysis.

Module details

In this module, we will focus on Python programming fundamentals. The aim is to help understand Python's basic syntax, data types, and operators, enabling the creation of simple programs. Additionally, we will cover the use of if statements, loops, and proper indentation to control program flow, fostering a foundational understanding of essential control structures in Python programming.

What's included

5 videos7 readings1 assignment1 programming assignment1 discussion prompt

5 videosTotal 19 minutes

Meet Your Faculty1 minute
Course Overview2 minutes
Python Fundamentals8 minutes
Control Structures Pt 13 minutes
Control Structures Pt 26 minutes

7 readingsTotal 59 minutes

Course Introduction2 minutes
Course Syllabus-Foundations of Data Analytics5 minutes
Academic Integrity1 minute
Python Fundamentals25 minutes
Control Structures Pt 110 minutes
Control Structures Pt 215 minutes
Module Summary1 minute

1 assignmentTotal 45 minutes

Week 1 Quiz45 minutes

1 programming assignmentTotal 200 minutes

Week 1: Hands On Session Lab200 minutes

1 discussion promptTotal 20 minutes

Meet Your Fellow Learners20 minutes

In this module, we will dive into the diverse landscape of Python data structures, including lists, dictionaries, sets, tuples, and arrays. By exploring real-world use cases, you will uncover the unique strengths and weaknesses of each data structure. You will gain insights into recognizing and understanding the characteristics of these structures, empowering you to make informed choices when tackling programming challenges. Through hands-on practice, you will develop the skills to select and apply the most suitable data structure to efficiently solve a wide range of problems, enhancing your proficiency in Python programming.

What's included

2 videos3 readings1 assignment1 programming assignment

In this module we will introduce DataFrames, a pivotal tool in data manipulation and analysis. You will grasp the fundamental concepts of DataFrames, learning how to create, manipulate, and access data efficiently. You will gain essential skills for basic data exploration–including summarizing data, indexing, and slicing, enabling them to extract meaningful insights. Furthermore, this module equips learners with the expertise to clean and preprocess data, covering handling missing values, filtering data, merging/joining datasets, and transforming data for analysis readiness. By the end of this module, you will harness DataFrames for advanced data analysis, mastering group-wise operations, aggregation, and statistical analysis.

What's included

3 videos4 readings1 assignment1 programming assignment

3 videosTotal 19 minutes

Introduction to DataFrames9 minutes
Data Cleaning and Transformation5 minutes
Data Aggregation5 minutes

4 readingsTotal 17 minutes

Introduction to DataFrames1 minute
Data Cleaning and Transformation10 minutes
Data Aggregation5 minutes
Module Summary1 minute

1 assignmentTotal 45 minutes

Week 3 Quiz45 minutes

1 programming assignmentTotal 200 minutes

Week 3: Hands On Session Lab200 minutes

This module will equip you with a comprehensive toolkit for proficient data exploration and analysis. It covers the essential techniques and tools for effectively summarizing data sets, encompassing statistical summaries, data visualization, and data cleaning methods. You will learn how to identify and assess missing data, outliers, and anomalies, vital tasks during the initial exploratory phase of data analysis. Furthermore, you will develop the ability to uncover patterns, relationships, and trends within the data using various visualizations, including scatter plots, histograms, and correlation matrices, enabling them to extract valuable insights and make informed decisions from their data.

What's included

2 videos2 readings1 assignment1 programming assignment

Prepare for a degree

Taking this course by Northeastern University may provide you with a preview of the topics, materials and instructors in a related degree program which can help you decide if the topic or university is right for you.