Data Analytics Course
ROICIANS
Course Information
| Level | Intermediate |
| Batch Availability | Weekdays, Weekend |
| Mode of Class | Classroom, Online, Hybrid |
| Duration | 39 hours |
Enquiry Form
Key Features
Hands-on Learning Program
Get trained from working professional
Get trained as per market Trend
work on live projects
Training on all latest tools and skill
Continuous Interview preparation
Complete job assistance (Canada only)
Mock interview session from working QA professionals
Course Overview
Our Data Analytics Course is designed to provide Practical Learning and implementation of all the end-to-end lifecycle of a Data Analytics project. We Train on the latest tools related to Data Analytics that match the Latest Data Analyst Jobs Description. This course is indented to provide both communications and technical learning.
- Candidate should have Bachelor degree or college diploma in Computer Science/Information
Technology/Computer Applications/ Computer engineering. - One should be good team player.
- Anyone who wants to start in the IT industry.
- Anyone who wants to enhance their career as Data Analyst.
- Data Analysts who want practical implementation and enhance their knowledge on latest tools.
- Anyone with no or minimal IT Experience.
- Anyone who wants a stable career in IT industry.
- If you don’t have IT Experience but want to get into IT.
- If you Know Data Analytics, but are not getting any interview calls
- Plenty of job opportunities, as data is increasing day by day, and the demand for Data Analysts is
also increasing tremendously. - If you do not possess any IT experience, you can still easily obtain a Junior Data Analyst position.
- Salary range is increasing dramatically day by day.
- There is no ‘dead-end’ job search period for a Data Analyst, as it is always in high demand.
- Get trained from Working Professionals with years of expertise: We have Specialist who knows market trend and latest tools and will train you on Live working projects
- We offer Java training from basics to required level: Keeping in mind that even Non IT individual also join this, we provide training on Java from basic to advance, so no prior knowledge is required in java
- We provide daily interview sessions according to current market: We believe training is only beneficial, if you can fetch job. So our specialists prepare students for interviews from day one. We prepare you for all interview Questions that could be asked
- Evaluation and interview from technical recruiters: We call technical recruiters to evaluate you, these are the people who actually hires in companies. So they Check whether you can pull it up or not.
- Training on different web based Live applications: We provide practical Training on Live projects, so that you can learn what practical scenarios for Selenium Testing could be. This helps a lot in interviews
- Training on all latest frameworks and browsers: Selenium is all about creating Frameworks and working on different browsers, so along with Live Projects, student will be creating their own frameworks.
COURSE CURRICULUM
• Create a Data Server
• Login to your Data Server
• Create a Data Analytics environment on your Data Server
- Python3 & Jupyter notebook
- Bash
- Install Python libraries relevant to Data Analytics
- Install csvkit for Bash
• Working with directories
• Using Bash to download a 7-million-row dataset
• Exploring raw data using Bash
• Options in Bash for wordcount
• Piping in Bash
• ‘grep’ in Bash
• Variables in Bash
• Looping in Bash
- ‘while’ loop in Bash scripts
- ‘if’ statements
• Regular Expressions in Bash
• Working with ‘dates’ in Bash
• Descriptive Statistics
- Measures of Central Tendency
- Measures of Dispersion
- Measures of Relationship
• Inferential statistics
- 4 techniques of Population Sampling
• Types of data
• 6 stages of the Analytics Methodology
• Introduction to Databases and SQL
• DDL statements
• DML statements
• Aggregation functions, GROUP BY
• CTE’s
• JOINs
• Single-Line Functions
- String functions
- Date and Time functions
- Numeric functions
• UNIONS
• MINUS
• INTERSECT
• CASE
• COALESCE
• Window functions
• Datatypes in Python
• Loops & conditional statements
• User-defined functions
• Variables
• Built-in functions
• Objects in Python
- Mutable objects:
❖ List
❖ Dictionary
❖ Numpy arrays - Immutable objects:
❖ Strings
❖ Tuples
• Operations on Numpy arrays
• Using Pandas
• Data Visualization using Python
• Data Cleaning process
• EDA (Exploratory Data Analysis) process
• Exploring Time Series data
• 4 Methods for Time Series forecasting
• Adjustments and Transformations on Time Series data
• Predictive Modelling methods:
- Overview of common ML algorithms
- Regression:
❖ Intro to Linear Regression
❖ Interpreting Regression results - Building the best ML model
- Feature Engineering
- Dummy variables
- Classification approach:
❖ k-NN algorithm
• Intro to PowerBI
- Get data spreadsheets
- Power Query Editor
- Joining tables
- DAX
- Adding new measures
- Format data
- Transform data
- Buttons, Themes,
- Filters, Slicers, visualizations
• Employee Demographics dashboard
• Survey Data dashboard