This learning track provides hands-on application of Programming Constructs, Data Structures and prominent Data Science Libraries in Python; Data Handling, Descriptive Analysis, Predictive Modelling and Text Analysis in Python.
Develop a working understanding of Data Management and Data Pre-processing techniques using Python so as to prepare data for further analysis.
Develop a working understanding of the basics of statistical analysis and hypothesis testing that is used primarily in the domain of finance, marketing, clinical research etc. for validating the claims.
Learn to implement the different functionalities within the various Python libraries used in Data Science like Pandas, NumPy, Seaborn, Matplotlib etc. for data manipulation, visualization and analysis purposes.
Learn to implement the different techniques of data pre-processing, descriptive analysis, dimensionality reduction, predictive modelling and text analysis using Python.
What’s included
Shareable Certificate
Earn a sharable certificate upon completion
Lifetime Access
Access this learning track for life once completed
Flexible Scheduling
Start learning online immediately, at your own pace
Desktop Only
We recommend completing this learning track on a desktop
Skills you will learn
Python
Data Management
Data Pre-processing
Data Visualizations
Data Mining
Pandas
NumPy
Seaborn
Hypothesis Testing
EDA
Supervised Machine Learning
Statistical Analysis
Boosting
Clustering
PCA
Neural Networks
Text Analytics
Sentiment Analysis
Matplotlib
Syllabus
Fundamentals of Data Processing in Python
Data Science with Pandas
NumPy for Data Science
Getting started with Matplotlib
Data Visualization with Seaborn
Univariate Exploratory Data Analysis using Python
Multivariate Exploratory Data Analysis using Python Hypothesis Testing in Python
Feature Engineering in Python Simple Linear Regression using Python
Multiple Linear Regression using Python
Logistic Regression in Python
Support Vector Machines in Python
Naïve Bayes in Python
Tree Models in Python
Boosting Algorithms in Python
Clustering Algorithms in Python
PCA in Python
Artificial Neural Networks in Python
Convolutional Neural Networks in Python
Recurrent Neural Networks in Python
Introduction to Text processing in Python
ML Models for Text Data in Python
Sentiment Analysis in Python
How it Works
Learn new skills that will boost your career by enrolling in courses across data analytics, data science, ML and AI. These courses will utilize readings, videos, quizzes, data cases, and even coding exercises to teach you skills and concepts in a way that will solidify your new knowledge for hands-on application.
With our hands-on projects, you will take your newly learned skills along with our 750+ low-code/no-code functions and embedded coding console to complete milestone-based projects. Once completed, you will have effectively applied new skills and concepts to real-world data cases that can be translated directly into your career.
Complete assessments and track your progress in real-time to benchmark your proficiency in relation to key functional areas. As you progress through your courses, our patented platform will utilize ML and AI to record and analyze your inputs and output to provide active feedback and recommendations that will help you learn more effectively than the standard Letter Grade system used today.
Complete courses to earn sharable certificates and badges. These awarded items will be look great in your portfolio as you showcase your skills and project experience to employers and colleagues.
Learner Outcomes
Complete learning tracks to earn sharable certificates and badges. These awarded items will look great in your portfolio as you showcase your skills, projects, and experience to employers and colleagues.
The learner will be able to understand and apply different tools and techniques for data management, visualization, transformations, treatment, pre-processing, feature engineering and dimensionality reduction using Python.
The learner will be able to understand, identify and apply a suitable statistical test to verify the various hypotheses formulated for the problem in-hand.
The learner will be to identify and apply various Machine Learning (Supervised, Unsupervised, Text Analysis) techniques to real world data from different industries to generate business insights.
The learner will be able to implement different functionalities within the various Python libraries like Pandas, NumPy, Seaborn, Matplotlib etc. for data manipulation, visualization and analysis purposes.
The learner will be able to interpret and visualize the outcome of the various applied techniques.
WHAT THE COMMUNITY SAYS ABOUT US
“Rolai is the best program available for someone looking to enhance their skills”
Connor McEachron
Planning & Analytics @ Brooks Brothers
WHAT THE COMMUNITY SAYS ABOUT US
“Great way to learn data analytics and data science”
Balaji Reddy
Manager – Applications Development
WHAT THE COMMUNITY SAYS ABOUT US
“The courses were excellent and covered topics that I didn’t expect”
Aadarsha G
Student At Ohio Wesleyan University
All the Most Frequently Asked Questions
What People Are Asking About Data Education
Signing up is easy! Get Started from the homepage, just click the “Get Started” button to sign up instantly no credit card required.
Individual access is free. Business and Academia access require a subscription.
Our courses range from Beginner to Advanced. We have courses and learning tracks that are available for beginners, we do however recommend having a basic level of analytics before starting any beginner course.
You can sign up for a demo on the For Business Tab
Rolai’s patented process provides a personalized learning process for each user. Rolai goes deeper than simply learning concepts and testing your skills. At Rolai, learners can apply their skills to actual industry use cases and projects.
Course Catalog 
Resources 
Difficulty: Intermediate
Duration: Approximately 6 months
