Data Analytics Course Training in Vizag

Dive into the World of Data Analytics in Vizag

Data analytics is a key pillar in guiding decision-making and encouraging corporate growth in a time when data is the new currency. We help you explore the world of data analytics at our training facility in Vizag by breaking down difficult concepts into manageable chunks.

Why Choose softenant technologies for Your Data Analytics Training

For those looking to master data analytics, Softenant Technologies, based in the tech-friendly city of Visakhapatnam (Vizag), provides a vibrant learning environment. The following are the main justifications for why selecting Softenant for your data analytics training could be the most important choice you ever make for your career:

1. Industry-Recognized Curriculum:

We worked with industry professionals to create our data analytics course. This guarantees that our curriculum follows the most recent business trends, giving you the abilities that companies value.

2. Expert Faculty:

At Softenant Technologies, you'll learn from seasoned experts who are skilled at breaking down complicated ideas into easily digestible chunks. Their professional expertise gives the academic components of the course a context in the actual world.

3. Hands-On Learning:

We place a big emphasis on practical learning in our data analytics courses. Our course format includes real-world projects that give you the chance to put the knowledge you've learnt into practise.

4. State-of-the-Art Facilities:

To create a supportive learning environment, Softenant Technologies offers cutting-edge learning facilities. An engaging and successful learning experience is made possible by our cutting-edge resources.

5. Job Placement Assistance:

We are aware that our trainees want to find promising work possibilities in addition to learning data analytics. Softenant Technologies offers support with finding a work, assisting you in navigating the job market and locating a position that is a good fit for your abilities.

6. Networking Opportunities:

By joining Softenant Technologies, you can access a large network of professionals and students. Future learning, employment prospects, and professional development may all benefit greatly from this.

7. Location Advantage:

Softenant Technologies is in close proximity to several IT enterprises thanks to its location in Vizag, a city with a developing IT industry. This facilitates a smoother transition from your training to a professional position in the city.

A progressive, industry-aligned, and encouraging learning environment that is dedicated to your success is what you get when you choose Softenant Technologies for your data analytics training. Join us and advance your career in data analytics.

Overview of Our Comprehensive Data Analytics Course in Vizag

Our Data Analytics course at Softenant Technologies is created to give you the knowledge and abilities you need to succeed in this fast-paced industry. Let's explore the details of our programme:

Course Duration and Structure

Our 4-month intensive Data Analytics course is a programme. Its framework is intended to provide you a thorough understanding of the fundamental ideas behind data analytics. We employ a blended learning strategy that combines formal classroom instruction with hands-on lab work, group projects, and individual tasks. The course is designed to steadily advance your skills, starting with fundamental concepts and moving on to more complicated data analytics topics.

Key Components of Our Data Analytics Course in Visakhapatnam

Our data analytics course in Visakhapatnam is created to give you the tools and knowledge that are most in demand in the market. The following are the main elements of our extensive programme:

Module 1: Introduction to Data Analytics

  • Overview of data analytics and its significance in the digital era

  • The role of data analytics in business decision-making and strategy

  • Types of data analytics: descriptive, diagnostic, predictive, and prescriptive analytics

  • Understanding the data analytics lifecycle and iterative processes

  • Data-driven decision making and its impact on organizational performance

  • Introduction to data analytics tools and technologies

  • Key statistical concepts for data analytics: measures of central tendency, variability, and correlation

  • Ethical considerations in data analytics: privacy, security, and responsible data usage

  • Introduction to data governance and data quality management

  • Data visualization principles and best practices

  • Real-world examples and case studies showcasing the power of data analytics

  • Industry trends and emerging technologies in data analytics

  • Career opportunities and skill requirements in the field of data analytics

  • Introduction to programming concepts for data analytics

  • Data analytics challenges and how to overcome them effectively

Module 2: Excel for Data Analysis and Visualization

  • Introduction to Microsoft Excel and its applications in data analytics

  • Data importing and cleaning techniques in Excel

  • Working with formulas and functions for data manipulation and analysis

  • Advanced data manipulation techniques: sorting, filtering, and conditional formatting

  • Pivot tables and pivot charts for data summarization and analysis

  • Advanced charting techniques for effective data visualization

  • Using Excel add-ins for statistical analysis and advanced analytics

  • Data validation and cleansing techniques in Excel

  • Collaborative data analysis using Excel's collaboration features

  • Excel's Power Query for data extraction, transformation, and loading (ETL)

  • Advanced data modeling techniques in Excel

  • Automation and macros in Excel for streamlining data analysis tasks

  • Advanced Excel functions for statistical analysis and regression modeling

  • Simulating scenarios and performing sensitivity analysis in Excel

  • Excel tips and tricks for efficient data analysis and visualization

Module 3: SQL for Data Management and Querying

  • Introduction to relational databases and their role in data management

  • Understanding the SQL language and its components

  • Creating and managing database tables using SQL

  • Performing data queries using SELECT statements

  • Filtering and sorting data with WHERE and ORDER BY clauses

  • Joining multiple tables using different types of joins

  • Grouping and aggregating data using GROUP BY and aggregate functions

  • Subqueries and correlated subqueries for advanced data retrieval

  • Modifying data with INSERT, UPDATE, and DELETE statements

  • Working with views and stored procedures in SQL

  • SQL functions for data manipulation and transformation

  • Indexing and optimizing SQL queries for performance

  • Handling NULL values and data integrity constraints in SQL

  • Transaction management and data security in SQL databases

  • Advanced SQL topics: window functions, common table expressions, and recursive queries

Module 4: Python for Data Analytics

  • Introduction to Python and its applications in data analytics

  • Python basics: variables, data types, operators, and control structures

  • Reading and writing data files using Python

  • Data preprocessing and cleaning with Python libraries (e.g., Pandas)

  • Exploratory data analysis (EDA) with Python

  • Data visualization using Python libraries (e.g., Matplotlib, Seaborn)

  • Statistical analysis with Python libraries (e.g., SciPy, StatsModels)

  • Handling missing data and outliers in Python

  • Data aggregation and grouping in Python

  • Feature engineering and selection in Python

  • Introduction to machine learning with Python (Scikit-learn)

  • Regression analysis and predictive modeling with Python

  • Classification techniques and model evaluation in Python

  • Clustering and dimensionality reduction in Python

  • Text analytics and natural language processing (NLP) with Python

Module 5: Introduction to Machine Learning

  • Overview of machine learning concepts and applications

  • Supervised learning algorithms: regression and classification

  • Unsupervised learning algorithms: clustering and dimensionality reduction

  • Model training, evaluation, and validation techniques

  • Feature engineering and feature selection in machine learning

  • Decision trees and random forests

  • Support Vector Machines (SVM)

  • Naive Bayes classification

  • Neural networks and deep learning basics

  • Evaluation metrics for classification and regression models

  • Ensemble learning techniques: bagging and boosting

  • Introduction to recommendation systems and collaborative filtering

  • Handling imbalanced datasets in machine learning

  • Introduction to reinforcement learning and its applications

  • Deploying and monitoring machine learning models

Module 6: Power BI for Interactive Data Visualization

  • Introduction to Power BI and its capabilities in data visualization

  • Connecting to data sources and importing data into Power BI

  • Transforming and cleaning data using Power Query Editor

  • Building data models and relationships in Power BI Desktop

  • Creating interactive visualizations using Power BI visuals

  • Designing effective dashboards and reports in Power BI

  • Applying filters, slicers, and drill-through in Power BI

  • Advanced data modeling techniques using DAX expressions

  • Creating calculated columns and measures in Power BI

  • Data storytelling and interactive features in Power BI

  • Advanced visuals and custom visuals in Power BI

  • Sharing and collaboration features in Power BI

  • Power BI Mobile app and real-time data monitoring

  • Power BI Gateway for data refresh and on-premises data access

  • Power BI best practices for performance optimization and security

Module 7: Tableau for Advanced Visualizations and Dashboards

  • Introduction to Tableau and its role in data visualization

  • Connecting to data sources and importing data into Tableau

  • Creating basic visualizations in Tableau (e.g., bar charts, line charts)

  • Advanced visualization techniques in Tableau (e.g., treemaps, heat maps)

  • Applying filters, parameters, and calculated fields in Tableau

  • Creating interactive dashboards and storyboarding in Tableau

  • Advanced analytics and forecasting in Tableau

  • Working with maps and spatial data in Tableau

  • Blending and aggregating data from multiple sources in Tableau

  • Advanced calculations and table calculations in Tableau

  • Implementing Level of Detail (LOD) expressions in Tableau

  • Customizing and formatting visualizations in Tableau

  • Tableau Server and online collaboration features

  • Publishing and sharing Tableau workbooks and dashboards

  • Tableau best practices for performance optimization and design aesthetics

Module 8: Data Analytics in Practice

  • Applying data analytics techniques to real-world datasets and scenarios

  • Case studies and examples from various industries (e.g., finance, marketing, healthcare)

  • Data exploration and analysis using selected tools (e.g., Excel, SQL, Python)

  • Data visualization and storytelling for effective communication of insights

  • Data-driven decision making and problem-solving methodologies

  • Handling unstructured and semi-structured data in data analytics projects

  • Introduction to big data analytics and technologies (e.g., Hadoop, Spark)

  • Real-time analytics and streaming data processing

  • Data analytics for customer segmentation and targeting

  • Fraud detection and anomaly detection using data analytics techniques

  • Sentiment analysis and social media analytics

  • Time series analysis and forecasting in data analytics

  • A/B testing and experimentation in data-driven decision making

  • Data analytics project management and lifecycle

  • Collaboration and teamwork in data analytics projects

Module 9: Communication and Presentation Skills

  • Effective storytelling with data and the art of data-driven narratives

  • Principles of data visualization and design aesthetics

  • Selecting appropriate visualizations for different types of data

  • Communicating insights to non-technical stakeholders effectively

  • Creating compelling data presentations and reports

  • Interpreting and explaining data analysis results clearly

  • Data-driven decision-making techniques and frameworks

  • Communicating uncertainty and limitations in data analysis

  • Ethical considerations in data reporting and presentation

  • Data privacy and confidentiality in data communication

  • Public speaking and presentation skills for data professionals

  • Effective use of presentation tools and technologies

  • Data visualization and storytelling case studies

  • Presenting data insights to different types of audiences

  • Handling questions and feedback during data presentations

Module 10: Capstone Project

  • Undertaking a comprehensive data analytics project from start to finish

  • Identifying a real-world problem or scenario for data analysis

  • Data collection, preprocessing, and cleaning

  • Applying relevant data analytics tools and techniques

  • Designing and creating interactive visualizations and dashboards

  • Deriving insights and making data-driven recommendations

  • Documenting and presenting project findings and insights

  • Peer evaluation and feedback on capstone projects

  • Showcasing capstone projects to industry professionals (optional)

  • Reflection and lessons learned from the capstone experience

Frequently Asked Questions About Our Data Analytics Course

It can be difficult to understand the details of our course and navigate the data analytics environment. We answer a few of the frequently asked questions below that may assist you in reaching a wise decision:

Who can enroll in the Data Analytics course in Vizag?

Anyone interested in data analytics is welcome to enrol in our programme. This includes recent graduates, working professionals seeking to advance their skills, and people with non-technical backgrounds who are eager to enter the tech sector. Although not required, having a basic understanding of mathematics and a computer language can be helpful.

What is the duration of the course?

The data analytics course is a four-month programme with weekday class times. We also provide working professionals with weekend batches.

What is the mode of teaching for the course?

A mixed learning strategy is used to deliver the course. This covers classroom instruction, online resources, hands-on lab sessions, and cooperative group projects. Data Science Course in Vizag

Will I receive a certificate upon completion of the course?

You will obtain a Data Analytics Certification from Softenant Technologies after successfully completing the course. The computer industry often accepts this qualification.

Are there any placement opportunities after completing the course?

Softenant Technologies does offer help with job placement. Each student receives individualised attention from our dedicated placement cell, which offers advice and assistance with job searching, interview prep, and professional network building.

What tools and technologies are taught in the course?

Several tools and technologies that are crucial for a data analyst are covered in our course. This includes big data technologies like Hadoop and Spark, computer languages like Python and R, SQL for database management, and tools for data visualisation like Tableau and PowerBI.

Can I balance the course with my full-time job or studies?

The course was created with both students and working professionals in mind. You can balance your career or studies while pursuing the course thanks to flexible scheduling options and weekend classes.

For any other queries, feel free to get in touch with us. We're here to help you embark on your data analytics journey!

Career Opportunities After Completing Our Data Analytics Course in Vizag

Our goal at Softenant Technologies goes beyond merely teaching you skills; we also help you become ready for a rewarding career in data analytics. Following completion of our course, you can expect to have the following job opportunities:

Job Placement Assistance and Internship Opportunities

A dedicated placement cell at Softenant Technologies offers thorough help with job placement. You will get advice on creating a CV, preparing for interviews, and job searching as part of our Data Analytics course. Our partnerships with leading businesses in Vizag and around the nation frequently lead to internship opportunities for our students. These internships can prepare you for full-time work and provide you with practical work experience.

Skills Required for Top Data Analytics Jobs

Our data analytics course is meant to provide you the abilities needed to succeed in top data analytics positions. These consist of:

• Expertise with coding languages like Python and R.

• SQL and database management know-how.

• The capacity to do statistical analysis and interpret data.

• Proven ability to visualise data using programmes like Tableau and PowerBI.

• Knowledge of machine learning and AI principles.

• The capacity to work with huge datasets using tools like Spark and Hadoop.

When hiring for data analytics positions, companies look for these abilities, and our course makes sure you have a strong grasp of them.

Future Prospects for Data Analysts in Vizag

Vizag has promising future opportunities for data analysts due to its quickly expanding tech sector. To fully utilise the power of data, businesses in the city—both startups and big corporations—are always looking for qualified data analysts. Data analysts are essential to the success of these businesses because they provide recommendations, forecast trends, and provide information for strategic decisions. By completing our Data Analytics course in Vizag, you are better equipped to take advantage of these prospects and establish a successful career.

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