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Data Scientist
This learning track introduces the concepts and techniques of Data Treatment, Data Transformations, Data Visualizations, Feature Engineering, Descriptive and Predictive Analysis, Supervised and Unsupervised Machine Learning, ML Model Development, Hyperparameter tuning, Evaluation and Selection, and Ensemble Learning.
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29 Courses
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10 Projects & Case Studies
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Difficulty: Advanced
Prior knowledge or professional experience is highly recommended
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Duration: Approximately 9 Months
Suggested learning pace is 5hr/week
Track Overview
- Learn various Data Management and Data Transformation techniques to fetch data from different tables and convert them to useable format to improve data inputs to Machine Learning models.
- Learn Data Pre-processing methods for noise removal through outliers and missing value analysis, basics of Data Visualization and other tools & techniques for Univariate & Multivariate data analysis.
- Learn the concepts and various techniques of Supervised Machine Learning, Unsupervised Machine Learning and Ensemble Learning focussing on building an ML model, Hyperparameter optimization, Model Evaluation and Selection.
- Learn the application of data science concepts and techniques across fields, and how data analysis can help in making data driven decisions.
What’s included
Lifetime Access
Access this case study 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
- Fundamentals of Data Analytics
- Introduction to ANOVA
- Fundamentals of Data Pre-processing
- Data Mining Concepts and Techniques
- Basic Data Visualization Methods
- Advanced Feature Engineering Techniques
- Data Aggregation Techniques
- Data Transformation Techniques
- Machine Learning – Logistic Regression
- Model Evaluation Techniques
- Basics of Hyperparameter Tuning – Linear & Logistic Regression
- Getting Started with Naive Bayes Classifier
- Support Vector Machines in ML
- Hyperparameter Tuning in SVM
- Understanding Decision Trees
- Hyperparameter Tuning in Tree-Based Models
- Bagging and Random Forest in Machine Learning
- Concepts and Application of Objective and Subjective Segmentation
- Understanding Principal Component Analysis
- Data preprocessing on used cars data
- Exploratory Data Analysis on Vehicle Crash data & Fatalities
- Data preprocessing on used cars data
- Analyzing Customer Rating On Voice Call Quality Across Different Regions
- Application Of EDA On Vehicle Inventory For An Online Auction Portal
- Applying Linear Regression to predict used car prices
- Loan Amount prediction for different applications using Regression Techniques
- Predicting failure of Power Transformers in a Manufacturing plant using Regression & Performing Root Cause Analysis
- Predicting Heart Disease with Logistic Regression
- Using Naïve Bayes Classifier To Predict Water Potability
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 shareable certificates and badges. These awarded items will look great in your portfolio as you showcase your skills, projects, and experience to employers and colleagues.
- Gain an understanding of and apply different tools and techniques for data management, visualization, transformations, treatment, pre-processing, feature engineering and dimensionality reduction.
- Evaluation and selection of appropriate supervised, unsupervised or ensemble machine learning technique(s) for predictive modeling.
- Identification and application of various machine learning techniques to real world data from different industries to generate business insights.
- Interpret and visualize the outcome of the various applied techniques.
“Rolai provides contextual upskilling opportunities … on one single platform.”
“An excellent tool for anyone who wants to quickly learn the ropes.”
“Rolai is the best program available for someone looking to enhance their skills”
“Great way to learn data analytics and data science”
“The courses were excellent and covered topics that I didn’t expect”
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.
Our courses include readings, videos, quizzes, and hands-on data cases that are completed using our virtual lab; give learners an applied learning experience.
No additional tools are needed to begin learning with Rolai. Our virtual lab contains the necessary data workspace and an embedded coding console.
- We have internal SMEs across industries and domains that we work with to develop relevant content and assure quality datasets and problem statements.
- We also work with enterprises and universities to develop new content directed towards their industry and expertise.
