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Data Analytics Training in Bangalore

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  • Classes at Beginner and Advanced Levels
  • Data Analytics Through Practical Experience
  • 17,402+ Students Trained and 350+ Employing Clients
  • Provided by a 9+ Years of Data Analytics Certified Expert
  • Permanent Access to the Study Materials and Student Portal
  • Next Data Analytics Batch to Begin This Week – Enroll Your Name Now!

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Upcoming Batches


Weekdays Regular

08:00 AM & 10:00 AM Batches

(Class 1Hr - 1:30Hrs) / Per Session


Weekdays Regular

08:00 AM & 10:00 AM Batches

(Class 1Hr - 1:30Hrs) / Per Session


Weekend Regular

(10:00 AM - 01:30 PM)

(Class 3hr - 3:30Hrs) / Per Session


Weekend Fasttrack

(09:00 AM - 02:00 PM)

(Class 4:30Hr - 5:00Hrs) / Per Session

Hear it from our Graduate

Have Cracked Their Dream Job in Top MNC Companies

Learn the Best Practices With Our Data Analytics Course

  • The first part of our course covers the fundamental concepts of data analysis, such as data types, data structures, and elementary statistical methods. This foundation will help us comprehend more complex subjects later on.
  • Completion of our course verifies knowledge of data analysis methods, tools, and techniques. It improves prospects for employment in disciplines like data science, business intelligence, and decision-making.
  • Our data analytics course covers big data handling technologies like Hadoop, Spark, and distributed computing frameworks because of the growing amount and complexity of data.
  • After completing this course, we help students get placed. This covers preparing for interviews, creating resumes, and helping students find jobs through collaborations with businesses in the industry.
  • Our data analytics course uses real-world data sets for practical projects. This hands-on learning opportunity develops problem-solving abilities and offers an understanding of data challenges in various domains.
  • Typically, this course is taught by seasoned professionals with relevant industry experience and a solid foundation in data analytics. Many of our trainers have advanced degrees in data science, computer science, or statistics.
  • Graduates of the Data Analytics Course can work in various fields, including marketing, e-commerce, finance, and healthcare. Possible job titles include data scientists, business analysts, data analysts, and analytics consultants.
  • Classroom Batch Training
  • One To One Training
  • Online Training
  • Customized Training
  • Enroll Now

Course Objectives

  • Statistical Analysis
  • Data Cleaning and Preprocessing
  • Data Visualization
  • Advanced Analytics Techniques
  • Big Data Technologies
  • Database Management and SQL
  • Basics of Machine Learning
Professionals can progress in their careers by landing jobs as data scientists, business analysts, analytics consultants, or analysts after completing a data analytics training. They can anticipate opportunities for increased pay, professional advancement, and the capacity to make significant contributions to organizations through data-driven insights and decision-making.
  • Creating insightful visualizations
  • Machine learning model implementation and assessment for categorization and predictive analytics activities
  • Real-world Datasets
  • Building interactive dashboards to showcase analytical results and insights
  • R
  • Python
  • Scala
  • Julia
  • SQL
Yes, because data analytics is in high demand across industries, it is a high-paying job. Programming, statistics, and data analysis specialists can command high compensation, particularly in industries like e-commerce, finance, technology, and healthcare, where making decisions based on data is essential to success.
  • Apache Hadoop
  • Apache Spark
  • Tableau
  • SAS
  • Power BI
Enrolling in a Data Analytics training is advised since it provides people with the necessary abilities to glean insights from data, supporting decision-making processes in a variety of industries. In today's data-driven world, being proficient in data manipulation, analysis, and visualization is essential for career advancement.

Is it easy to learn Data Analytics?

Depending on one's background, level of commitment, and concept complexity, learning data analytics can be challenging in different ways. Even though it necessitates a strong foundation in statistics, programming, and data manipulation, motivated learners can succeed with dedication and the help of resources like online tutorials and training.

What prerequisites must be met to enroll in a Data Analytics training?

  • Basic Computer Skills
  • Familiarity with programming languages
  • understanding of basic mathematical ideas
  • Understanding of data structures, data types, and data manipulation methods

Will Data Analytics Trends Drive the IT Sector in the Future?

Yes, future trends in data analytics will play a major role in driving the IT industry. Businesses will increasingly rely on analytics to obtain insights, optimize operations, and make data-driven decisions as a result of the exponential growth of data, which will create a strong demand for qualified individuals in this sector.

What advantages come with obtaining a Data Analytics certification?

  • Career Advancement
  • Industry Recognition
  • Prospective Pay
  • Skill Validation
  • Personal Development
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An Overview of Data Analytics

Data analytics is a cross-disciplinary domain focused on examining, refining, converting, and modeling data to uncover valuable insights, inform decisions, and drive actions. It encompasses diverse methodologies like statistical analysis, machine learning, and predictive modeling applied to vast and intricate datasets. Widely adopted across industries such as business, healthcare, finance, and marketing, data analytics facilitates the identification of patterns, trends, and relationships crucial for strategic planning and operational optimization. With the advent of big data and technological advancements like cloud computing and artificial intelligence, data analytics remains dynamic, empowering organizations to gain competitive advantages through data-driven innovation, enhanced efficiencies, and informed decision-making processes.


Additional Info

Trends and Emerging Technologies in the Future of Data Analytics

  • Edge Analytics: Due to the growth of Internet of Things (IoT) devices, data is being generated at the network's edge. On these devices or gateways, edge analytics processes data locally, minimizing latency and bandwidth consumption and facilitating real-time insights and actions.
  • Augmented Analytics: Augmented analytics uses AI and ML technologies to automate data preparation, insight production, and natural language processing (NLP) in analytics applications, making analytics more accessible to non-technical users. It improves decision-making by offering useful, actionable insights in an approachable way.
  • DataOps: The DataOps methodology places a strong emphasis on teamwork, automation, and the integration of analytics and data operations procedures. Applying DevOps principles to data analytics workflows aims to expedite time-to-insight, improve data quality, and streamline data pipelines.
  • Blockchain in Data Analytics: Blockchain technology ensures data security and integrity by providing decentralized, immutable data storage. It can be used in data analytics to facilitate transparent and auditable data transactions, fostering accountability and trust in procedures involving data sharing.
  • Graph Analytics: Supply chain optimization, fraud detection, social network analysis, and recommendation systems can all benefit from the use of graph analytics, which focuses on examining the connections and relationships between data points. It extracts knowledge from intricate relational data structures.
  • Privacy-Preserving Analytics: Privacy-preserving analytics methods like federated learning, homomorphic encryption, and differential privacy are becoming more popular as worries about data privacy and compliance with laws like the CCPA and GDPR grow. These techniques allow for data analysis without jeopardizing personal privacy.
  • Real-time Analytics: Making timely decisions in today's fast-paced business environment is becoming increasingly dependent on real-time analytics. Stream processing, event-driven architectures, and in-memory computing are examples of technologies that let businesses analyze and act on data as it is generated.
  • Hybrid and Multi-cloud Analytics: In order to avoid vendor lock-in and take advantage of the advantages offered by multiple cloud providers, organizations are implementing hybrid and multi-cloud strategies. Analytics platforms that are hybrid or multi-cloud enable smooth data integration and analysis in dispersed environments.

Explore the Popular Tools Used in Data Analytics

  • Tableau: A potent data visualization tool that uses a variety of data sources, Tableau lets users create interactive dashboards and reports. It makes data exploration and sharing insights with stakeholders easier.
  • Jupyter Notebook: This open-source web application makes interactive computing and data analysis possible. It combines text, code, and visuals into a single document and supports several programming languages, such as Python and R.
  • Apache Spark: Apache Spark is a quick and scalable data processing engine that supports batch processing, streaming, machine learning, and graph processing. Because of its distributed computing capabilities, it is well-liked for big data analytics.
  • Excel: Excel is still a widely used tool for simple data analysis, reporting, and visualization tasks despite its simplicity. Users from a variety of industries can utilize it because of its user-friendly interface and spreadsheet features.
  • MATLAB: MATLAB is an environment and programming language for numerical analysis and visualization. It is extensively utilized for data analysis, signal processing, and simulation in scientific and engineering research.
  • SAS: A software suite called SAS (Statistical Analysis System) is used for multivariate analysis, predictive modeling, and advanced analytics. It provides a huge selection of tools and solutions for statistical analysis, reporting, and data management in many industries.

Reasons to Choose Data Analytics Training

  • In-Demand Skills: Our data analytics training equips individuals with in-demand skills like machine learning, statistical analysis, data mining, and data visualization in today's data-driven economy.
  • Versatility: Data analytics expertise is useful in a variety of professions and fields. A strong foundation in data analytics can benefit any career path, including operations, finance, marketing, and technology.
  • Strategic Decision-Making: After their acquisition of insights from extensive, complex datasets, individuals who undergo training in data analytics are more qualified to make data-driven judgments. Businesses rely on data analysts to identify trends, patterns, and correlations that help with strategic planning and company goals.
  • Continuous Learning and Development: The data analytics field is continuously changing due to the introduction of new tools, techniques, and technologies. Those who receive data analytics training can stay up to date on the newest developments in the industry and lay the groundwork for lifetime learning and professional growth.
  • Global Demand: The worldwide demand for data analytics skills has created job and career advancement opportunities in both domestic and foreign markets. Companies worldwide are in search of proficient data analysts who can stimulate innovation and provide them with a competitive edge.
  • High Earning Potential: Worldwide demand for data analytics skills has created job and career advancement opportunities in both home and foreign markets. Companies worldwide are in search of proficient data analysts who can stimulate innovation and provide them with a competitive edge.

Career Paths for Certified Data Analytics Professionals

  • Data Analyst: Data is gathered, processed, and analyzed by data analysts to find patterns and insights that guide business choices. They use a variety of instruments and methods to prepare, organize, and present data so stakeholders can get useful information.
  • Business Intelligence Analyst: They analyze data to provide strategic insights and support organizational decision-making. They create and manage reports, dashboards, and data visualizations to share trends and key performance metrics with business stakeholders.
  • Data Scientist: They create predictive models and derive insights from data by utilizing sophisticated statistical and machine learning techniques. They work with intricate data sets to find trends, create algorithms, and provide data-driven suggestions for enhancing and optimizing business operations.
  • Data Engineer: They create, construct, and manage infrastructure and data pipelines to guarantee effective data processing, storage, and gathering. To support data-driven initiatives and guarantee data quality and reliability, they collaborate closely with data scientists and analysts.
  • Machine Learning Engineer: In order to address business challenges, machine learning engineers concentrate on creating and implementing machine learning models and algorithms. To increase accuracy and performance, they work with massive data sets, plan experiments, and optimize algorithms.
  • Data Architect: Data architects create and implement the general arrangement and structure of data inside an organization. They create data models, specify data standards, and set up data governance guidelines to guarantee data integrity, security, and accessibility.
  • Data Visualization Specialist: Experts in data visualization produce captivating visuals and interactive dashboards that make difficult data insights understandable and approachable. They create and develop visualizations that aid in comprehension and decision-making using programs like Tableau, Power BI, and D3.js.
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Key Features

ACTE Bangalore offers Data Analytics Training in more than 27+ branches with expert trainers. Here are the key features,

  • 40 Hours Course Duration
  • 100% Job Oriented Training
  • Industry Expert Faculties
  • Free Demo Class Available
  • Completed 500+ Batches
  • Certification Guidance

Authorized Partners

ACTE TRAINING INSTITUTE PVT LTD is the unique Authorised Oracle Partner, Authorised Microsoft Partner, Authorised Pearson Vue Exam Center, Authorised PSI Exam Center, Authorised Partner Of AWS and National Institute of Education (nie) Admedabad.


Syllabus of Data Analytics Training in Bangalore
Module 1: Foundations of Data Analysis
  • Static Analysis
  • Counting, Probability, and Probability Distributions
  • Sampling Distributions
  • Estimation and Hypothesis Testing
Module 2: Exploratory Data Analysis
  • Scatter Diagram
  • ANOVA and Chi-square
  • Data Cleaning
  • Correlation and Regression
  • Imputation Techniques
Module 3: Data Analytics Overview
  • Importance of Data Analytics
  • Descriptive Analytics
  • Diagnostic Analytics
  • Predictive Analytics
  • Prescriptive Analytics
  • Benefits of Data Analytics
Module 4: Data Visualization
  • Graphical Techniques
  • Data Types, Measure Of central tendency, Measures of Dispersion
  • Skewness & Kurtosis
  • Box Plot
  • Data Visualization Tools
Module 5: Basic Excel for Data Analysis
  • The CONCATENATE Function
  • Absolute Cell References
  • Data Validation
  • Conditional Formatting
  • Using the IF Function
  • Pivot Tables
  • Charts
  • Difference between Tables and Ranges
  • Create Table
  • Removing Unwanted Characters from Text
Module 6: Advanced Excel for Data Analysis
  • Date Formats
  • Conditional Formatting
  • Filtering
  • Lookup Functions
  • Sorting
  • Pivoting
Module 7: Structured Query Language (SQL)
  • SQL SELECT Statement
  • Usage of Single-Row Functions
  • Invoke Conversion Functions
  • Conditional Expressions
  • Aggregate Data Using the Group Functions
  • Display Data From Multiple Tables Using Joins
  • Use Sub-queries to Solve Queries
  • The SET Operators
  • Data Manipulation Statements
  • Use of DDL Statements to Create and Manage Tables
  • Management of Schema Objects
  • Manipulate Large Data Sets
  • Data Management in Different Time Zones
  • Retrieve Data Using Sub-queries
  • Regular Expression Support
Module 8: Data Visualization Tools- Power BI
  • Introduction to Power BI
  • Power BI Desktop
  • Data Source Connection
  • Data Transforming
  • Modeling using Power BI
  • Data Visualization
  • Reports and Dashboards
  • Publishing and Sharing Reports
Module 9: Data Visualization Tools- Tableau
  • Tableau Basic Reports
  • Tableau Charts
  • Tableau Advanced Reports
  • Calculations & Filters
  • Tableau Dashboards
  • Server
Module 10: Python for Data Analysis
  • Basics of Python
  • Program Flow / Data Flow
  • Functions
  • File Handling
  • Exception Handling
  • OOP Concepts
  • Comprehension in Python
  • Thread and DateTime
  • Advanced data Structure/collections
  • GUI programming with Python
  • API access with Python
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Need customized curriculum?

Get Hands-on Knowledge about Real-Time Data Analytics Projects

Project 1
Time Series Forecasting

In this project, students involve in predicting future values based on historical data patterns, crucial for forecasting trends and making decisions.

Project 2
Exploratory Data Analysis

Students analyze and visualize datasets to identify patterns, trends, and relationships using tools like Python's Pandas, Matplotlib, and Seaborn libraries.

Get Acquire Our Resourceful Data Analytics Job Support Program

  • Our Data Analytics job assistance program frequently starts with helping people enhance their resumes to highlight pertinent training, experience, and abilities in the field of data analytics.
  • Interview preparation is a crucial component of our job assistance program. It contains practice questions, advice on frequently asked topics, and methods for successfully demonstrating data analytics abilities.
  • To help with goal clarification, job opportunity identification, and the creation of customized career strategies in data analytics, our data analytics job support provides individualized career counseling.
  • Due to our student's solid relationships with trustworthy companies like Google, Microsoft, Uber, LinkedIn, Salesforce, Netflix, and IBM, placements in large, international corporations are made possible.
  • Our job support program offers workshops to enhance skills in data analytics, including machine learning, statistics, data visualization, and programming in Python and R, boosting employability.
  • Our job assistance program includes organizing networking events, connecting participants with alumni or business professionals, and offering tools for developing a professional network.

Sustain Our Intelligent Data Analytics Certification

Our certification in data analytics demonstrates your ability to analyze, interpret, and draw conclusions from data to inform business choices. It includes abilities like programming, machine learning, data visualization, and statistical analysis. To prove competency, certification programs usually include hands-on instruction, tests, and real-world projects. Obtaining certification improves one's employability and career prospects in the rapidly developing data analytics industry.

A data analytics certification will help you advance your career by proving that you are an expert in the field, gaining you more credibility with employers, opening up more job opportunities, and raising your pay. As a result of their expertise in using data analysis to support well-informed business decisions, certified professionals are highly valued in today's data-driven environment.
Undoubtedly, a data analytics certification significantly enhances your job prospects. Employers often prefer candidates with certified data analysis skills, increasing your chances of securing roles in data-driven sectors such as marketing, technology, healthcare, finance, and advertising.
  • Data Analyst
  • Data Scientist
  • Big Data Engineer
  • Data Visualization Specialist
  • Database Administrator
  • Data Engineer
  • Machine Learning Engineer
  • Big Data Analytics Certification
  • Business Intelligence (BI) Certification
  • Data Science Certification
  • Data Engineering Certification
The length of time needed to earn a data analytics certification varies based on the particular program as well as the background knowledge and experience of the candidate. Certification courses normally take a few weeks to several months to complete, though some intense boot camps offer accelerated options.

Complete Your Course

a downloadable Certificate in PDF format, immediately available to you when you complete your Course

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a physical version of your officially branded and security-marked Certificate.

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Get Train With Our Effective Data Analytics Instructor

  • Statistical analysis, data visualization, machine learning, and programming languages like Python and R are just a few of the areas in which our data analytics instructor excels.
  • They use a variety of teaching strategies, including lectures, practical exercises, case studies, and real-world projects, to support learning and the practical application of data analytics concepts.
  • Because they work for major corporations like Google, Microsoft, Netflix, Amazon, and Uber, all of our data analytics instructors bring a wealth of real-world experience to the classroom.
  • Our instructor not only teaches technical skills but also provides career guidance and advice to help students navigate job opportunities, craft a compelling CV, and get ready for data analytics interviews.
  • Our instructors for data analytics training in Bangalore have real-world experience working in the field, which enables them to impart to their students practical knowledge, examples, and best practices.
  • Our instructors provide individualized guidance and support throughout the learning process, adapting their teaching style to each student's particular needs and ability levels.
  • Data analytics instructor ensures they deliver current and pertinent instruction by staying up to date with the newest trends, tools, and techniques in the field through ongoing professional development and learning.

Data Analytics Course FAQs

Are you looking for a better deal at a lower price?

Give +91 93833 99991 a call right now to see what amazing offers are waiting for you!
  • ACTE extends support to its students by offering placement assistance
  • The placement cell provides continuous support until students successfully secure employment
  • ACTE fosters robust relationships with more than 700 renowned MNCs, ensuring abundant placement prospects
  • Gain complimentary lifetime access to the Student Portal for access to job listings, study materials, instructional videos, recorded sessions, and popular MNC interview questions
  • With an impressive placement rate exceeding 85%, ACTE showcases its commitment to student achievement
  • Students can validate placements by consulting the Placed Student list on the website
ACTE is widely recognized since it has a history of assisting students in obtaining employment at esteemed MNCs like SAP, Oracle, and Accenture. With an amazing 85% placement rate and over 3500 students placed overseas in the previous year, ACTE promises a wealth of resources and support for career advancement.
Yes, there are hands-on training components in the data analytics course. Students apply theoretical concepts, analyze datasets, and develop data-driven solutions through practical exercises, real-world projects, and case studies. This gives them invaluable experience with data analytics tools and techniques.
Every trainer at ACTE is a working professional with ten to sixteen years of relevant IT experience. They can offer a fantastic learning opportunity since they are subject matter experts with training from ACTE. Our trainers use real-world experiences and useful examples to improve learning and ensure that students receive top-notch training that prepares them for the workforce.
If you are unable to attend in person, you can use ACTE to view the recorded classes. You can access study materials and communicate with the teacher for continued guidance and support via our Student Portal.
Because our course can be taken online, in a classroom, one-on-one, fast-tracked, modified, or customized, it can be easily managed with your real-life obligations.

Why Should I Enroll in an ACTE Data Analytics Course?

Taking an ACTE data analytics course has many advantages. Learn from knowledgeable instructors, acquire real-world experience through hands-on training, gain access to industry-relevant curriculum, get help finding employment, and enjoy lifetime resource access. With ACTE's demonstrated track record of success, you're making an investment in the advancement of your career.
It is possible for prospective students to visit ACTE for an orientation or trial class prior to enrolling. It enables people to interact with instructors, experience the teaching style, and assess the course material before deciding whether or not to enroll.
The National Institute of Education (NIE), located in Singapore, will award you with the internationally recognized ACTE course completion certification.
Leading training organization ACTE has been offering top-notch instruction in a number of subjects, including Data Analytics, for more than 15 years, earning a reputation as a reliable educational resource.
Although this varies, classes normally consist of 10 to 20 students in each batch. This keeps the student-teacher ratio at the optimal level for learning and makes it possible for students to receive individualized attention from teachers.
There are usually options for morning, afternoon, or evening classes offered on weekdays or weekends. The length of the course, the instructor's availability, and the student's may all affect the schedule.
You can contact our support number at +91 93800 99996 / Directly can do by's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India
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