Data Analytics

6 courses

Intro to Data Analysis with Python

Learn the fundamental programming skills of a Data Analyst with this beginner-friendly learning path. Use Python libraries to clean, analyze, and visualize data. These 6 fun courses will help your kick-start your Data Analytics career.

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This learning path includes:

6 courses with bite-sized lessons and practices

30 engaging lessons in text and video formats

131 hands-on practices

One-on-one guidance from Cosmo, our AI tutor

Verified skills you'll gain

ADVANCED

Coding and Data Algorithms

ADVANCED

Data Cleaning and Preprocessing

DEVELOPING

Data Analysis for Insights

INTERMEDIATE

Data Visualization and Reporting

Tools you'll use

MatPlotLib

Numpy

Pandas

Python

SciPy

Seaborn

Trusted by learners working at top companies

6 lessons

24 practices

Python Libraries for Data Analysis

Immerse yourself in the world of Python’s powerful libraries used for Data Analysis. This course covers the installation and operation of the numpy and pandas libraries. Delve into the practical application of these libraries with special focus on creating and manipulating numpy arrays and pandas dataframes.

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5 lessons

24 practices

Descriptive and Inferential Statistics with Python

Take a deep dive into the fascinating world of statistics using Python with this well-curated course. It focuses on the calculation and practical application of descriptive and inferential statistics using Python's pandas, numpy, and scipy libraries.

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5 lessons

24 practices

Data Cleaning and Preprocessing Techniques

Embarking on this course allows you to deeply understand and apply data cleaning and preprocessing techniques. It systematically covers the concepts of data cleaning, handling missing values, normalization, binning, encoding, and more, aiming to equip you with practical skills for preparing data for analysis or machine learning tasks.

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4 lessons

18 practices

Advanced Preprocessing and Collecting Techniques

This course delves deeper into advanced data preprocessing and collection techniques with an extensive focus on merging DataFrames, grouping, and sorting values. It aims to provide an in-depth comprehension of these techniques, preparing the learners to effectively manage, transform, and prepare complex datasets for analysis.

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4 lessons

15 practices

Hypothesis Testing with Python

Embark on your journey to mastering Hypothesis Testing with Python in this comprehensive course. It thoroughly covers how to conduct a variety of statistical tests, analyze and interpret results, enabling you to make data-driven decisions and inferences.

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6 lessons

26 practices

Reporting and Visualization for Data Analysts

This course transports you to the captivating world of Data Visualization and Reporting. It extensively familiarizes you with various techniques and tools for creating meaningful, interactive and visually appealing reports and dashboards using libraries like Matplotlib and Seaborn.

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Meet Cosmo: The smartest AI guide in the universe

Our built-in AI guide and tutor, Cosmo, prompts you with challenges that are built just for you and unblocks you when you get stuck.

Whether you’re leveling up or just starting out, find your next step here.