Data Analytics Bootcamp
Available courses
Learn to import, clean, pre-process and transform data in preparation for analytics, visualization, and modeling. You will learn the following tools;
- Pandas
- Data Cleaning
- Missing Values Treatment
- Handling Duplicates
- Dealing With outliers
- Visual Inspection and Dealing with Wrong Entries
- Dealing With Categorical Variables
- Data Preprocessing & Transformation
- SciKit Learn Library for;
- Rescaling
- Standardization
- Normalization
- SciKit Learn Library for;
- Feature Selection & Engineering
- Special Topics For Data Processing (SQL, Stats,and More)
Become A Data Science Professional In Under 8 Months!
The OneCampus Data Science Course equips you with the basic skills you need to start working on a variety of data science projects. You’ll work through the essential building blocks of a data science project gradually through this course and then put all the pieces together to consolidate your knowledge and apply your learning in the real world.
This program is covered 100% by a GATIP Scholarship
What you will learn
- Gain mastery of how to apply data science techniques to convert raw data into game-changing insights
- Multiple projects and exercises strengthen your skill to solve business problems using machine learning algorithms
- Learn how to assess model performance and improve model accuracy using ensemble techniques and hyper-parameter tuning
- Learn to wrangle data like a pro and create new features that better expose hidden concepts in the data to your algorithms
- Build the confidence to take on big data science projects and organize your work as a data science expert
Program Benefits
Through this course, participants will gain strong mastery of the full cycle of data science model development; from data preprocessing down to pushing trained/tested models to production. Key aspects of the course include:
- Explore the key differences between supervised learning and unsupervised learning
- Manipulate and analyze data using scikit-learn and pandas libraries
- Understand key concepts such as regression, classification, and clustering
- Discover advanced techniques to improve the accuracy of your model
- Understand how to speed up the process of adding new features
- Simplify your machine learning workflow for production
Requirements
- No previous knowledge required
Become a Qualified Data Analytics Professional in 6+ Months!
The OneCampus Data Analytics professional program is a comprehensive projects-based training that shows you how to analyze your data and gain insights into your business. Starting with the basics of data analysis, including data visualization and exploratory data analysis, this Masterclass takes you through 10 real-world projects that have been carefully choreographed to build and strengthen your mastery of the complete spectrum of tools, techniques, and tricks of a seasoned data analyst. This masterclass is the ideal learning path on your journey to becoming an expert data analyst.
This program is covered 100% by a GATIP Scholarship.
What you will learn
- learn how to discover these hidden patterns in your data
- Analyze patterns in data and leverage the results to help transform your organization
- Learn how to correlate data, plot histograms, and analyze temporal features
- Learn how to visualize data for your organization using the Seaborn and Matplotlib libraries
- Explore a variety of use cases that show you how to join and merge databases, prepare data for analysis, and handle imba...
- Learn different data analysis techniques, including hypothesis testing, correlation, and null-value imputation
- Become a confident data analyst with a certification to show
Program Benefits
Through this Bootcamp, participants will gain strong mastery of expert data analysis and visualization skills to solve business problems using state-of-the-art data analytics models. Key aspects of the course include:
- Get to grips with the fundamental concepts and conventions of data analysis
- Understand how different algorithms help you to analyze the data effectively
- Determine the variation between groups of data using hypothesis testing
- Visualize your data correctly using appropriate plotting points
- Use correlation techniques to uncover the relationship between variables
- Find hidden patterns in data using advanced techniques and strategies
- Learn how to analyze time series and categorical data.
Requirements
- This program does not require any previous familiarity with programming or analytics
Learn the fundamentals of Python programming language and build the skills required to succeed in a career in any of the data science domains Note: This course is part of the Python Academy and a required component of the learning track in the OneCampus Data Analytics, Data Science, and Machine Learning Professional Programs.
The Python Academy will prepare you for a career in data analytics, data science, and machine learning using Python as the core programing language. We will achieve this through the 6 stage Python learning cycle:
What learn
- Python Programming Environment Setup (Ananconda navigator and Virtual Environment)
- Introduction to Jupyter Notebook
- Introduction to Python and Python Variables and Comments
- Python Strings and String Functions
- Python Operators and Comparison Operators
- Python Data Types and Expressions
- Python Conditional Statement
- Python Loops and Decision Logic
- Python Containers (Tuples, Lists,Sets & Dictionaries)
- Python Date and Time
- Python Functions and Modules
- Special Topics (Classes, Exceptions, and more)
Data Analytics Professional Program Course Completion
Data Science Professional program course completion
Machine Learning Professional program Course Completion
Learn the fundamentals of Python programming language and build the skills required to succeed in a career in any of the data science domains Note: This course is part of the Python Academy and a required component of the learning track in the OneCampus Data Analytics, Data Science, and Machine Learning Professional Programs.
The Python Academy will prepare you for a career in data analytics, data science, and machine learning using Python as the core programing language. We will achieve this through the 6 stage Python learning cycle:
What learn
- Python Programming Environment Setup (Ananconda navigator and Virtual Environment)
- Introduction to Jupyter Notebook
- Introduction to Python and Python Variables and Comments
- Python Strings and String Functions
- Python Operators and Comparison Operators
- Python Data Types and Expressions
- Python Conditional Statement
- Python Loops and Decision Logic
- Python Containers (Tuples, Lists,Sets & Dictionaries)
- Python Date and Time
- Python Functions and Modules
- Special Topics (Classes, Exceptions, and more)
Learn the fundamentals of Python programming language and build the skills required to succeed in a career in any of the data science domains Note: This course is part of the Python Academy and a required component of the learning track in the OneCampus Data Analytics, Data Science, and Machine Learning Professional Programs.
The Python Academy will prepare you for a career in data analytics, data science, and machine learning using Python as the core programing language. We will achieve this through the 6 stage Python learning cycle:
What learn
- Python Programming Environment Setup (Ananconda navigator and Virtual Environment)
- Introduction to Jupyter Notebook
- Introduction to Python and Python Variables and Comments
- Python Strings and String Functions
- Python Operators and Comparison Operators
- Python Data Types and Expressions
- Python Conditional Statement
- Python Loops and Decision Logic
- Python Containers (Tuples, Lists,Sets & Dictionaries)
- Python Date and Time
- Python Functions and Modules
- Special Topics (Classes, Exceptions, and more)
Learn the fundamentals of Python programming language and build the skills required to succeed in a career in any of the data science domains Note: This course is part of the Python Academy and a required component of the learning track in the OneCampus Data Analytics, Data Science, and Machine Learning Professional Programs.
The Python Academy will prepare you for a career in data analytics, data science, and machine learning using Python as the core programing language. We will achieve this through the 6 stage Python learning cycle:
What learn
- Python Programming Environment Setup (Ananconda navigator and Virtual Environment)
- Introduction to Jupyter Notebook
- Introduction to Python and Python Variables and Comments
- Python Strings and String Functions
- Python Operators and Comparison Operators
- Python Data Types and Expressions
- Python Conditional Statement
- Python Loops and Decision Logic
- Python Containers (Tuples, Lists,Sets & Dictionaries)
- Python Date and Time
- Python Functions and Modules
- Special Topics (Classes, Exceptions, and more)
Learn the fundamentals of Python programming language and build the skills required to succeed in a career in any of the data science domains Note: This course is part of the Python Academy and a required component of the learning track in the OneCampus Data Analytics, Data Science, and Machine Learning Professional Programs.
The Python Academy will prepare you for a career in data analytics, data science, and machine learning using Python as the core programing language. We will achieve this through the 6 stage Python learning cycle:
What learn
- Python Programming Environment Setup (Ananconda navigator and Virtual Environment)
- Introduction to Jupyter Notebook
- Introduction to Python and Python Variables and Comments
- Python Strings and String Functions
- Python Operators and Comparison Operators
- Python Data Types and Expressions
- Python Conditional Statement
- Python Loops and Decision Logic
- Python Containers (Tuples, Lists,Sets & Dictionaries)
- Python Date and Time
- Python Functions and Modules
- Special Topics (Classes, Exceptions, and more)
Learn the fundamentals of Python programming language and build the skills required to succeed in a career in any of the data science domains Note: This course is part of the Python Academy and a required component of the learning track in the OneCampus Data Analytics, Data Science, and Machine Learning Professional Programs.
The Python Academy will prepare you for a career in data analytics, data science, and machine learning using Python as the core programing language. We will achieve this through the 6 stage Python learning cycle:
What learn
- Python Programming Environment Setup (Ananconda navigator and Virtual Environment)
- Introduction to Jupyter Notebook
- Introduction to Python and Python Variables and Comments
- Python Strings and String Functions
- Python Operators and Comparison Operators
- Python Data Types and Expressions
- Python Conditional Statement
- Python Loops and Decision Logic
- Python Containers (Tuples, Lists,Sets & Dictionaries)
- Python Date and Time
- Python Functions and Modules
- Special Topics (Classes, Exceptions, and more)
Learn to import, clean, pre-process and transform data in preparation for analytics, visualization, and modeling. You will learn the following tools;
- Pandas
- Data Cleaning
- Missing Values Treatment
- Handling Duplicates
- Dealing With outliers
- Visual Inspection and Dealing with Wrong Entries
- Dealing With Categorical Variables
- Data Preprocessing & Transformation
- SciKit Learn Library for;
- Rescaling
- Standardization
- Normalization
- SciKit Learn Library for;
- Feature Selection & Engineering
- Special Topics For Data Processing (SQL, Stats,and More)
Learn to import, clean, pre-process and transform data in preparation for analytics, visualization, and modeling. You will learn the following tools;
- Pandas
- Data Cleaning
- Missing Values Treatment
- Handling Duplicates
- Dealing With outliers
- Visual Inspection and Dealing with Wrong Entries
- Dealing With Categorical Variables
- Data Preprocessing & Transformation
- SciKit Learn Library for;
- Rescaling
- Standardization
- Normalization
- SciKit Learn Library for;
- Feature Selection & Engineering
- Special Topics For Data Processing (SQL, Stats,and More)
Data visualization is the visual presentation of data or information. The goal of data visualization is to communicate data or information clearly and effectively to readers. Typically, data is visualized in the form of a chart, infographic, diagram or map.
- Identify trends and outliers
- Tell a story within the data
- Reinforce an argument or opinion
- Highlight an important point in a set of data
- Generate Insights locked in the data
- Build sharable dashboards
- Matplot Library
- Bokeh
- Seaborn
- ggplot
- Plotly
- Dash
- Advanced Tools
What you will learn
✅ Get a functional mastery of a balanced set of data visualization tools.✅ Work with different plotting libraries and get to know their strengths and weaknesses.
✅ Master data visualization techniques and use cases
✅ Design and develop data visualization specifications for use cases.
✅ Learn the art of storytelling with data visualization.
✅ Build a visualization dashboard.
✅ deploy visualizations dynamically.
Repo contains materials and links to external materials that may be used by students
General datasets for student use