Data Analytics Online Course With 100% Placement Support
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Data Analytics Online Course

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Live Instructor LED Online Training

Learn from Certified Experts

  • Data Analytics with Practical Experience
  • Classes for Beginner and Advanced Levels
  • 17,402+ Students Trained, 350+ Employing Clients
  • Provided by 8+ years of certified data analytics expert
  • Permanent Access to the Study Materials and Student Portal
  • Next Data Analytics starting 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

Get the Best Practices with Our data analytics online course

  • The first section of our training covers essential ideas in data analysis, such as data types, data structures, and basic statistical approaches. This foundation will help us understand more difficult topics later on.
  • Seasoned individuals with relevant industry expertise and a thorough understanding of data analytics often teach this training. Many of our trainees hold graduate degrees in data science, computer science, and statistics.
  • Because of the increasing volume and complexity of data, our data analytics training includes big data handling technologies such as Hadoop, Spark, and distributed computing frameworks.
  • We assist students in finding employment when they have completed this training. This includes interview preparation, résumé creation, and job placement assistance through industry collaborations.
  • Real-world data sets are used in our data analytics online course to complete practical projects. This hands-on learning experience improves problem-solving skills and provides an awareness of data difficulties across several areas.
  • Completing this training certifies your understanding of data analysis methodologies, tools, and strategies. It enhances career chances in fields such as data science, business intelligence, and decision-making.
  • Data analytics online course graduates can pursue careers in 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,
  • SQL,
  • machine learning basics.

Following completion of a data analytics school, professionals can further their careers by working as data scientists, business analysts, analytics consultants, or analysts. They can anticipate prospects for higher income, professional growth, and the ability to make major contributions to businesses via data-driven insights and decision-making.

  • Creating intelligent visuals.
  • Implementing and evaluating machine learning models for classification and predictive analytics.
  • Real-World Datasets
  • Creating dynamic dashboards to highlight analytical results and insights.
  • R
  • Python
  • Scala
  • Julia
  • SQL

Yes, because data analytics is in high demand across sectors, it is a well-paid position. Programming, statistics, and data analysis professionals may command high salaries, especially in areas such as e-commerce, banking, technology, and healthcare, where data-driven choices are critical to success.

  • Tableau
  • Power BI
  • Apache Hadoop
  • Apache Spark
  • SAS

Enrolling in a Data Analytics course is recommended because it equips workers with the skills needed to extract insights from data, which aids decision-making processes in a range of sectors. In today's data-driven environment, being skilled at data manipulation, analysis, and visualization is critical for job growth.

Is it simple to learn data analytics?

Learning data analytics may be tough in a variety of ways, depending on one's background, amount of dedication, and idea complexity. Even though it requires a solid foundation in statistics, programming, and data manipulation, dedicated students may achieve with dedication and tools such as online tutorials and courses.

What criteria must be satisfied before enrolling in a data analytics course?

  • Basic computer skills.
  • Experience with programming languages
  • Understanding of basic mathematical concepts
  • Knowledge of data structures, data kinds, and data manipulation techniques

Will Data Analytics Trends Drive IT in the Future?

Yes, future advances in data analytics will significantly impact the IT business. As data grows exponentially, businesses will increasingly rely on analytics to gain insights, improve operations, and make data-driven choices, resulting in a high need for competent professionals in this industry.

What are the advantages of earning a Data Analytics certification?

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

Data analytics is the process of evaluating raw data to derive conclusions about it. It entails using statistical analysis and machine learning approaches to identify patterns, trends, correlations, and other insights in datasets. Organizations may use these insights to make better decisions, solve problems, and enhance operations. Data analytics involves several processes, including data gathering, cleansing, analysis, and visualization. During the data-gathering phase, relevant information is acquired from a variety of sources, including databases, spreadsheets, sensors, social media, and more. Data cleaning entails preparing and refining the acquired information to guarantee correctness and consistency.


Additional Info

Future Trends and Emerging Technologies for Data Analytics

  • AI and Machine Learning Advancements: As artificial intelligence (AI) and machine learning (ML) algorithms improve, more complex data analysis capabilities will emerge.
  • Edge Computing: As the number of Internet of Things (IoT) devices grows, edge computing will become more crucial for processing data closer to its source. This strategy decreases latency and bandwidth utilization, allowing for real-time analytics and decision-making in remote contexts.
  • Augmented Analytics: Augmented analytics incorporates AI and machine learning technology into analytics tools to automate data preparation, insight finding, and interpretation. Natural language processing and automated insights production will allow non-technical people to extract meaningful insights from data more effectively.
  • Data Privacy and Ethics: As data privacy legislation tightens and concerns about data ethics develop, there will be an increased emphasis on incorporating privacy-preserving techniques and ethical norms into data analytics operations.
  • Explainable AI (XAI): As AI models become more widely used in important decision-making processes, there is a rising demand for AI systems that are transparent and interpretable. Explainable AI approaches will help consumers comprehend how AI algorithms make predictions or judgments, increasing trust and responsibility.
  • Graph Analytics: Graph analytics will become popular for evaluating interconnected data structures, including social networks, supply chains, and cybersecurity networks. Graph databases and algorithms will help companies discover hidden linkages, recognize trends, and conduct intricate network research.
  • Automated Data Governance: As data quantities increase and data rules tighten, automated data governance solutions will be critical to assuring data quality, integrity, and compliance. Automated metadata management, data lineage tracking, and policy enforcement will improve data governance procedures.
  • Hybrid and Multi-cloud Data Management: Organizations will use hybrid and multi-cloud data management strategies to benefit from the scalability, agility, and cost-effectiveness of cloud platforms while keeping control over sensitive data and satisfying regulatory obligations.
  • Quantum Computing: Although still in its early stages, quantum computing has the potential to transform data analytics by addressing complicated optimization and simulation problems considerably quicker than traditional computers.
  • Continuous Intelligence: This approach integrates real-time analytics, event processing, and decision automation to provide proactive, context-aware insights and actions. Streaming analytics systems and complicated event processing engines will enable dynamic decision-making in fast-changing contexts like IoT, cybersecurity, and financial markets.

Discover the Most Popular Data Analytics Tools

    • Python: Python is a powerful programming language that includes several libraries for data processing, analysis, and visualization. Pandas, NumPy, and Matplotlib, are popular libraries for data processing and visualization, while scikit-learn offers a comprehensive ecosystem for machine learning methods.
    • R: R is a statistical programming language and environment created primarily for data analysis and visualization. It provides a diverse set of packages for statistical modeling, data manipulation, and graphical representation, making it a popular choice among statisticians and data scientists.
    • Structured Query Language (SQL):SQL is a standardized language for managing and accessing relational databases. It is required for obtaining, updating, and altering data contained in databases, making it an indispensable tool for data analysts and database managers.
    • Tableau: Tableau is a robust data visualization application that lets you build dynamic and visually appealing dashboards and reports. It supports a variety of data sources and provides simple drag-and-drop features for creating visuals, making it useful for data exploration and storytelling.
    • Microsoft Excel: Excel is a popular spreadsheet tool that provides basic data analysis and visualization features. It is widely used for easy data processing, graphing, and basic statistical analysis, notably in corporate contexts.
    • Power BI: Microsoft's business analytics application Power BI allows customers to see and share data findings. It has interactive dashboards, data interfaces, and complex analytics tools, making it appropriate for both self-service analytics and enterprise BI systems.
    • Apache Spark: Apache Spark is an open-source distributed computing platform for large-scale data processing. It has a single analytics engine for batch processing, streaming, machine learning, and graph processing, making it ideal for large-scale data analytics and processing.
    • Jupyter Notebook: Jupyter Notebook is an open-source web tool for creating and sharing documents with live code, equations, visualizations, and narrative prose.
    • SAS: SAS is a software suite that is commonly used for advanced analytics, corporate intelligence, and data management. Its complete range of capabilities for data manipulation, statistical analysis, predictive modeling, and reporting has made it popular in areas such as banking, healthcare, and government.
    • Apache Hadoop: Apache Hadoop is an open-source platform for distributing and analyzing big datasets across computer clusters.

    Career Options for Certified Data Analytics Professionals

    • Data Analyst: Data analysts gather, analyze, and interpret data in order to get insights that may be used to make decisions and build strategies.
    • Business Intelligence Analyst: Business intelligence analysts collect and analyze data to assist firms in making educated business choices.
    • Data Scientist: Data scientists extract insights from data using advanced analytical tools, machine learning algorithms, and predictive modeling to provide data-driven solutions to challenging business challenges.
    • Data Engineer: Data engineers develop, implement, and manage the infrastructure and systems required to enable data analytics and data-driven applications.
    • Data Architect: A data architect creates and implements an organization's entire data architecture and management plan.
    • Machine Learning Engineer: Machine learning engineers create and implement machine learning models and algorithms to tackle specific business issues.
    • Quantitative Analyst (Quant): Quantitative analysts, or quants, utilize mathematical and statistical tools to study financial markets, devise trading strategies, and predict risk.
    • Data Consultant: Data consultants advise firms on how to use data analytics to improve company performance and meet strategic goals.
    • Study Analyst: Research analysts conduct studies and analyses on certain subjects or sectors to help with decision-making and strategy creation.
    • Product Manager: Product managers utilize data analytics to guide product development and strategic decisions. They examine user behavior, market trends, and product performance data to find potential for product enhancements, new features, and market growth.
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Key Features

ACTE offers Selenium with Java 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) Singapore.


Curriculum For Data Analytics Online Course
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 (e.g., Power BI, Tableau)
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
  • 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?

Hands - On Projects For Data Analytics

Project 1
Exploratory Data Analysis (EDA)

Analyze real-world datasets across different domains. Use Pandas, Matplotlib, and Seaborn for data cleaning, visualization, and trend analysis.

Project 2
Natural Language Processing :

Perform sentiment analysis and topic modeling on text data. Implement NLP tasks using NLTK or spaCy libraries.

Acquire Our Reliable Data Analytics Placement Program

  • Our Data Analytics Placement program typically begins by helping clients improve their resumes to showcase relevant training, experience, and talents in data analytics.
  • Interview preparation is an important part of our placement program. It includes practice questions, tips on frequently asked questions, and strategies for effectively showing data analytics skills.
  • Our Data Analytics Placement assistance offers personalized career counseling to assist with goal definition, job opportunity identification, and the development of tailored career plans in data analytics.
  • Placements with significant worldwide firms are feasible because our students have strong contacts with reputable companies such as Google, Microsoft, Uber, LinkedIn, Salesforce, Netflix, and IBM.
  • Our placement program provides training to improve skills in data analytics, such as machine learning, statistics, data visualization, and Python and R programming, hence increasing employability.
  • Our placement aid program organizes networking events, connects participants with alums or business people, and provides resources for building a professional network.

Obtain Advanced Data Analytics Certification from Industry Experts

Our data analytics certification validates your ability to evaluate, understand, and draw inferences from data to inform business decisions. It covers skills such as programming, machine learning, data visualization, and statistical analysis. Hands-on education, examinations, and real-world projects are common components of certification programs that demonstrate proficiency. Certification increases one's employability and job opportunities in the fast-growing data analytics field.

A data analytics certification will help you develop your career by demonstrating your expertise in the subject, giving you greater credibility with employers, opening up additional work prospects, and increasing your salary. Certified experts are in great demand in today's data-driven world because of their ability to leverage data analysis to support well-informed business choices.

Unquestionably, a data analytics certification improves your work possibilities. Employers frequently favor applicants with certified data analysis abilities, which increases your chances of landing jobs in data-driven industries like 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 amount of time required to get a data analytics certification varies depending on the program and the candidate's prior knowledge and experience. Certification courses often take a few weeks to many months to complete; however, some extreme boot camps provide faster choices.

Complete Your Course

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

Get Certified

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

Get Certified

Get Training With Our Effective Data analytics Online Course Trainers

  • Our data analytics online course Trainers excel in a variety of disciplines, including statistical analysis, data visualization, machine learning, and programming languages such as Python and R.
  • They use a range of instructional methodologies, including lectures, practical exercises, case studies, and real-world projects, to help students learn and apply data analytics ideas.
  • Because they work for big organizations like Google, Microsoft, Netflix, Amazon, and Uber, all of our data analytics trainers bring extensive real-world expertise to the classroom.
  • Our data analytics online course Trainers teach technical skills and give students professional advice and direction to help them explore employment prospects, create a great CV, and prepare for data analytics interviews.
  • Our Data Analytics Trainers have real-world expertise in the sector, allowing them to share practical information, examples, and best practices with their students.
  • Our data analytics online course Trainers offer personalized advice and support throughout the learning process, tailoring their teaching style to each student's specific goals and skill levels.
  • Our trainers ensure that they give current and relevant education by remaining up to speed on the latest trends, tools, and approaches in the industry through continual professional development and learning.

Data Analytics Course FAQs

Are you seeking for a better deal for a lesser price?

Give +91 93833 99991 Call +91 93833 99991 immediately to find out what incredible deals are waiting for you!
  • ACTE is renowned for its placement assistance, helping students secure job opportunities.
  • It collaborates with over 700 multinational companies worldwide, including SAP, Oracle, Amazon, HCL, Wipro, Dell, Accenture, Google, CTS, TCS, and IBM.
  • Last year, over 3500 students were placed successfully in both India and abroad.
  • ACTE offers development sessions such as mock interviews and presentation skills to prepare students for challenging interviews.
  • With an impressive 85% placement record, ACTE ensures students are well-prepared for their careers. You can verify placements by checking the Placed Student list on the website.
  • The Placement Cell provides ongoing support until students secure placements in top MNCs.
  • Students have access to the Student Portal, offering lifetime resources including job openings, study materials, videos, recorded sessions, and top MNC interview questions.
ACTE is well-known for its track record of assisting students in obtaining positions at prestigious international businesses like as SAP, Oracle, and Accenture. ACTE promises a variety of tools and help for professional progression, with an impressive 85% placement record and over 3500 students placed overseas the previous year.
Yes, the data analytics course includes practical training. Students use case studies, practical exercises, and real-world projects to apply theoretical principles, evaluate datasets, and build data-driven solutions. As a consequence, they obtain great expertise with data analytics tools and approaches.
At ACTE, each trainer has 10 to 16 years of relevant technical experience and is a working professional. As subject matter experts with ACTE training, they may offer an outstanding learning opportunity. Our trainers enhance learning and ensure that students receive excellent education that prepares them for the workforce by drawing on their own experiences and practical examples.
If you miss one or more classes, ACTE offers recorded sessions through the Student Portal. You may access these recordings at any moment, ensuring that you do not fall behind. In addition, the site provides study resources and instructional videos to help you catch up..
The Data Analytics Course provides a variety of training formats, including online classes, classroom sessions, and self-paced learning with access to recorded sessions and study materials through the Student Portal.

Why should I take an ACTE Data Analytics course?

Taking an ACTE Data Analytics course offers you with tools such as study guides, session recordings, and interview advice, as well as professional training and placement support. ACTE promises great career prospects and help due to its collaborations with over 700 multinational corporations and placement record of more than 85%.
Prior to enrolling, prospective students are invited to attend an orientation or trial class at ACTE. Before deciding whether or not to enroll, students can communicate with professors, see the teaching style, and evaluate the course material.
The National Institute of Education (NIE), based in Singapore, will grant you the globally recognized ACTE course completion certification.
For more than 15 years, the leading training firm ACTE has provided great education in a variety of areas, including Data Analytics, and has built a strong reputation as a reliable source of information.
ACTE's small class sizes of 10 to 15 individuals ensure that each participant receives customized attention and successful learning.
On weekdays and weekends, sessions are often offered in the morning, afternoon, or evening. The timetable may change depending on the frequency of the course, the student, and the instructor's availability.
You can enroll by contacting our support number at +91 93800 99996, using's E-commerce payment system, or visiting one of the ACTE branches in India.
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