 Become a Certified Data Science Expert
Master relevant skills that’ll fast-track your career, from the comfort of your home!
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What you’ll learn ? You’re in for a wonderful experience in terms of learning. From understanding R Programming to working with datasets, to getting a hang of PowerBI & Data Analytics using Pandas and mastering Machine Learning. You'll find everything to help you take that big career leap.
Highlights
- Exclusive lessons from Industry Experts
- Expert guidance & support
- Codekata – Gamified coding Arena
- MicroARC – Quick Quizzes to enhance your skill
- Internationally recognized accreditation
Course Modules:
Introduction to Data Engineering and Bigdata
Introduction to Data Engineering and Bigdata
- 38 Exclusive Lessons
- 11 hrs
- English
- Introduction to Course
- Python Introduction and Installation
- Basic Syntax of Python
- Data Structures in Python
- Python Built-in Functions
- User Defined Functions in Python
- Modules and Packages in Python
- Introduction to Databases and MySQL Installation
- SQL-1
- SQL-2
- SQL-3
- SQL-4
- SQL Assignment
- Python Assignment
- Data Warehousing Concepts
- OLAP and its Operations
- Bigdata and Parallel Computing
- Hadoop and its Ecosystem
- HDFS Architecture and File Storage
- HDFS Installation and Commands
- HDFS Assignment
- Map Reduce and word count example
- Map Reduce Workflow
- Data Storage File Formats
- YARN
- Map Reduce Assignment
- Introduction to Apache Spark
- Spark Architecture and Toolkit
- Spark APIs : RDD
- Transformations and Actions
- Spark APIs: Distributed Shared Variables
- Spark APIs : Dataframes and Datasets
- Spark APIs : Spark SQL
- Spark Execution Modes
- Spark Application Life cycle and Tuning
- Spark Hands on Examples-1
- Spark Hands on Examples-2
- Spark Dataframe, RDD, Spark SQL Assignment
R programming
R programming
- 27 Exclusive Lessons
- 6 hrs
- English
- R - An Introduction
- Variables and Operators
- Vectors
- Matrices
- Lists
- Data Frames
- Factors and Datasets
- Summarise functions
- Conclusion
- Relational Operations
- Logical Operations
- Control Statements
- Looping Statements and Functions
- Mathematical and Statistical Relational Functions
- apply functions
- map functions
- Dplyr Select
- Dplyr - Slice, Mutate, Arrange
- data.table - Select, Filter and Sort
- Joins
- Grammar of Graphics
- Plots and Histograms
- Pie Charts
- ggplots
- Project Task
- Project Task Solution
- Final Assessment
Data Analytics using Pandas
Data Analytics using Pandas
- 16 Exclusive Lessons
- 3 hrs
- English
- Introduction
- Setting up Pandas Environment
- An Introduction to Jupyter Notebook
- Loading Data into Pandas
- A Deeper Look Into Data
- DataFrames - Basic Functions
- dataframes- rows and columns
- Sorting DataFrames
- Handling Datetime Fields in Pandas
- Statistical Functions in Pandas
- Pandas - Indexes
- Data Grouped Representation
- Data Visualization
- Adding New Data - Merge, Join
- Adding New Data - Append/Concat
- Final Project & End Note
Data visualization with Matplotlib in Python
Data visualization with Matplotlib in Python
- 34 Exclusive Lessons
- 7 hrs
- English
- Introduction to Matplotlib
- Installing Matplotlib and dependencies
- Setup - Jupyter Notebook
- Getting started with basic of Matplotlib
- Introduction to pyplot
- Adding Labels to plot
- Formatting plot style
- Specifying axis in plot
- Adding and customizing markers
- Adding Titles and Legends to a plot
- Scatter Plot and categorical plotting
- Scatter plot in matplotlib
- Plotting category categorical variables in various format
- Line and SETP method
- Assignment_1_Basics of Matplotlib
- Figure and Subplot in Matplotlib
- Concept of Figure and SubPlotting
- Plotting multiple figure and plots
- Applying Grids to the plot
- More Plots in Matplotlib
- Histograms in Matplotlib
- Bar charts in Matplotlib
- Pie Charts in Matplotlib
- Stack plots in Matplotlib
- Logarithmic plotting in Matplotlib
- Symlog and logit plot in Matplotlib
- Polar plot in Matplotlib
- Assignment_2_Intermediate knowledge of Matplotlib
- Working with Time-series data in matplotlib
- 3D Plotting and visualization in Matplotlib
- Working with Audio data in Matplotlib
- Working with images in matplotlib
- Saving plots as PNG and PDF file format in Matplotlib
- Assignment_3_Advance matplotlib knowledge
Data visualization in python
Data visualization in python
- 52 Exclusive Lessons
- 17 hrs
- English
- Introduction to Data Visualization
- Matplotlib for Data Visualization
- Using Matplotlib to draw plots
- Assignment on OO & Pyplot style in Matplotlib
- Visualizing & Customizing Plot appearances using Matplotlib
- Assignment on Plotting Basic plots using Matplotlib
- Multiple Line PLots
- Assignment on Drawing Multiple Line Plots
- Basics of Time Series Plotting
- Assignment on Time Series Plotting
- Time Series Plotting and adding styles to the plots
- Slicing and Customizing Time Series Data
- Assignment on Time Series slicing and plotting
- Twin Axes Plotting
- Bar Plot and Box Plots
- Assignment on Bar and Box Plots
- Voilin, Histogram and Scatter
- Assignment on Histogram and Scatter Plot
- Contour Plot and Annotations in Matplotlib
- Advance Annotations
- Assignment on annotations
- Image Tutorial in matplotlib
- Assignment on Image Tutorial
- Introduction to Seaborn Library
- Relational Plots and Subplots in Seaborn
- Subplotting in Rows and Columns using Relational Plot
- Assignment on Relational Plots in Seaborn
- Line Plots in Seaborn
- Assignment on Line Plots in Seaborn
- Bar Plots, Box Plots and Point Plots in Seaborn
- Assignment on Bar, Box and Line Plot
- Colour Palettes in Seaborn
- Introduction to BOKEH
- Assignment on Line and Bar Plotting in Bokeh
- Patch Plots and Scatter Marks in Bokeh
- Assignment on Patch Plots and Scatter Markers
- Area Plots and Circle Glyphs in Bokeh
- Assignment on Area Plots
- Rectangle, Oval and Polygon Glyphs in Bokeh
- Assignment on Rectangle, Oval and Polygon Glyphs
- Wedges, Arcs and Specialized curves in Bokeh
- Assignment on wedges, arcs and specialized curves in Bokeh
- Setting Plot ranges and Axes in Bokeh Plots
- Categorical and Log Axes in Bokeh
- Assignment on Bar plotting in Bokeh
- Twin Axes, Datetime axes and Annotations in Bokeh Plots
- Assignment on Twin, Datetime Axes
- Row and Column Layouts in Bokeh Plots
- Customizing Tools and Legends in Bokeh Plots
- Assignment on layout and Grid Plotting
- Column Data Source and Adding Widgets to Bokeh Plots
- Assignment on widgets in Bokeh Plots
Machine Learning 101
Machine Learning 101
- 17 Exclusive Lessons
- 3 hrs
- English
- About Machine Learning Course
- Installation of Anaconda
- What is Machine Learning
- Types of Machine Learning, Supervised Learning and Regression
- Types of ML,Logistic Regression and Unsupervised Learning
- SVM -What is SVM and How do they work
- SVM-Loading and Examining our dataset
- SVM-Building and Tweaking our SVM Classification mode
- What is Decision Tree?
- Building the Decision Tree : Decision Tree Learning
- Building a Decision Tree - Information Gain a Gini Impurity
- Decision Tree Lab:Building our First Decision Tree
- Decision Tree Lab:Viewing and Tweaking our Decision Tree
- What is Overfitting
- Random Forest Lab
- Teamwork
- Avoiding Overfitted Models
PowerBI Step by Step
PowerBI Step by Step
- 5 Exclusive Lessons
- 3 hrs
- English
Certificate
- Certificate will generate only after successful completion of course
- Certificate is generated for every course individually
- Certificates are auto generated
Our Happy Learners with Happier Careers
"I was new to programming, Python course in GUVI helped me to learn Python from basics. The videos were explaining the concepts very clearly and the Codekata platform made it interesting to spend time for learning."
- Arjun
"Interesting videos and way of teaching is very good. I could able to understand even advanced concepts with ease. It helped me to grow my skills as a developer. "
- Rishit
"My friend referred me GUVI. Initially I thought it is yet another E-learning site, after taking course in GUVI and solved programs in Codekata it proved that is not just a learning site but a platform that can leverage the skills. Codekata programs are defined very good and the interface is really cool."
- Agilan
Frequently asked questions
For how long can I access these courses?
You can access all these courses for 1 year.
Is it 100% online learning or should I come in person for any specific course?
It is a 100% online learning course package and there won’t be any necessity for you to be present in person.
Is there any particular order to learn these courses?
No. You can choose any course of your liking and you can go about with your preferred order.
What background knowledge should I possess?
You must possess the enthusiasm to enhance your knowledge, commitment to complete the courses and perseverance to achieve something monumental in life. Apart from this, you need not have any technical background knowledge.
What is the refund policy?
In case of dissatisfaction or due to any other such situations, you can claim for a refund within 7 days from the start of the course.
On what basis are the certificates rolled out?
The certificates are rolled out as and when you complete a course.
Will I gain access to any sort of Forum support?
Yes. You will gain complete access to our forum support to connect with our fellow aspiring users.
Apart from these courses, will I get access to any practise platforms?
You will gain access to CodeKata which is a gamified practice platform which hosts 1000+ curated coding problems and MicroARC, which is an interactive skill assessment platform which helps you to test your skills.
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