Expert Data Science Course in Hyderabad with Placement
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Data Science Course in Hyderabad

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  • Beginner & Advanced Data Science Classes
  • Over 14602+ Students Trained, with 340+ Job Opportunities
  • Gain Proficiency in Data Science through Practical Experience
  • Cost-effective Instruction and Curriculum Crafted by Industry Experts
  • Instructed by a Certified Data Science Expert with 7+ Years of Experience
  • Next Data Science Training Batch begins this week – Enroll Your Name Now!

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INR 14000


INR 22000

INR 18000

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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

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Have Cracked Their Dream Job in Top MNC Companies

Elevate Your Career with Our Data Science Training

  • Our Data Science training is meticulously designed to impart a comprehensive understanding of Data Science principles, practices, and real-world applications, essential in today's data-driven industries.
  • With our Data Science training, students can pursue rewarding careers in data analysis, machine learning, and various data science-related fields, equipped with highly sought-after skills across diverse industries.
  • Our Data Science training prioritizes hands-on learning through immersive exercises, practical projects, and industry-standard case studies, ensuring practical skill development aligned with current industry demands.
  • Through dedicated interview preparation sessions led by our Placement Support Team, students gain confidence and proficiency to excel in job interviews and secure promising opportunities in Data Science roles.
  • Advanced Data Science subjects include predictive modeling approaches, machine learning algorithms, and cutting-edge big data technologies like Apache Spark and Hadoop.
  • Data Science training offers a streamlined pathway for individuals aspiring to thrive in the dynamic realm of data analysis and machine learning. It provides essential skills and expertise tailored for success in the Data Science landscape.
  • Classroom Batch Training
  • One To One Training
  • Online Training
  • Customized Training
  • Enroll Now

Course Objectives

  • Collaborative Data Analysis
  • Automation Proficiency
  • Continuous Improvement
  • Scalability Enhancement

Absolutely, Data Science courses cater to beginners, providing foundational knowledge and skills necessary to enter the field. These courses cover fundamental concepts, tools, and practices, making them accessible to individuals with little to no prior experience in Data Science.

  • Data Analysis and Visualization
  • Machine Learning Algorithms
  • Statistical Modeling
  • Big Data Technologies like Apache Spark
  • Data Preprocessing Techniques

Yes, students in Data Science Training engage in real-world projects to apply their skills and gain practical experience. These projects simulate industry scenarios, allowing students to solve common challenges encountered in Data Science practices.

Boost your data analysis speed and precision while honing automation skills for streamlined data processing. Acquire in-demand Data Science expertise to broaden your career horizons in the fast-paced, data-driven industry. Stay at the forefront of this rapidly evolving field to seize emerging opportunities and maintain a competitive edge.

Indeed, there is a high demand for Data Science training due to the increasing reliance on data-driven decision-making across industries. Data Science training programs are sought after by individuals and organizations aiming to enhance their skills and stay competitive in the data-centric landscape.

  • Data Scientist
  • Machine Learning Engineer
  • Data Analyst
  • Business Intelligence Analyst
  • Big Data Engineer

What is the future scope of Data Science courses?

  • Continued Industry Relevance
  • Increased Adoption Across Sectors
  • Evolution of Tools and Technologies
  • Emphasis on Data Security and Privacy
  • Utilization in Hybrid and Multi-Cloud Environments

List the tools used in Data Science course?

  • Python Programming Language
  • R Programming Language
  • Jupyter Notebooks
  • Apache Spark
  • Tableau for Data Visualization

What Prerequisites are Required for Learning Data Science?

  • Basic understanding of statistics and mathematics.
  • Familiarity with programming languages like Python or R.
  • Understanding of data manipulation techniques.
  • Experience with data visualization tools.

Does Data Science need Coding?

Yes, Data Science often involves coding for tasks such as data preprocessing, algorithm implementation, and building predictive models. While not mandatory for all roles, coding skills greatly enhance a Data Scientist's ability to manipulate and analyze data effectively.

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Overview of Data Science

Data Science is an interdisciplinary field that utilizes scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It encompasses various techniques such as data mining, machine learning, and statistical analysis to uncover patterns, trends, and correlations. Data Scientists leverage programming languages like Python and R, along with tools like TensorFlow and Apache Spark, to analyze and interpret data. The insights derived from Data Science are utilized to inform business decisions, improve processes, and drive innovation across industries. With its increasing importance in today's digital age, Data Science offers vast career opportunities and plays a crucial role in shaping the future of technology and business.

Additional Information

Career Scope of Data Science

  • Diverse Industries: Data Scientists are in demand across industries such as healthcare, finance, retail, marketing, and technology, providing ample career options.
  • High Demand: With the increasing reliance on data-driven decision-making, the demand for Data Scientists is expected to continue rising, ensuring a steady stream of job opportunities.
  • Lucrative Salaries: Data Science roles command competitive salaries due to the specialized skills and expertise required, offering attractive compensation packages.
  • Career Advancement: Data Science offers opportunities for career growth and advancement, with pathways to senior and leadership positions such as Data Science Manager or Chief Data Officer.
  • Innovation: Data Scientists have the opportunity to work on cutting-edge projects and contribute to innovation through the development of predictive models, machine learning algorithms, and data-driven insights.
  • Global Opportunities: Data science abilities are in great demand worldwide, with several chances for international career progression and mobility. With a strong demand across sectors, Data Science experts may explore a wide range of employment marketplaces and pursue fulfilling careers all around the world.
  • Interdisciplinary Skills: Data Science professionals develop a diverse skill set encompassing statistics, programming, machine learning, and domain expertise, making them versatile and adaptable to various roles and industries.
  • Impactful Work: Data Scientists have the opportunity to make a significant impact by solving complex problems, driving business growth, and improving decision-making processes through data analysis and insights.

Roles and Responsibilities of the Data Science

  • Data Scientist: Data scientists are responsible for analyzing large volumes of data to extract actionable insights, developing predictive models using machine learning techniques, and effectively communicating their findings to stakeholders.
  • Machine Learning Engineer: Machine learning engineers focus on designing and optimizing machine learning algorithms and models, deploying these models into production environments, and collaborating closely with data scientists to ensure successful integration.
  • Data Analyst: Data analysts clean and explore data to identify trends and patterns, create reports and dashboards to present their findings, and support decision-making processes within organizations based on their data-driven insights.
  • Business Intelligence Analyst: Business intelligence analysts analyze business data to generate actionable insights, create visually appealing data visualizations and dashboards, and identify opportunities for process improvement and optimization.
  • Big Data Engineer: Big data engineers design, build, and maintain large-scale data processing systems, develop and optimize data pipelines for efficient data ingestion and processing, and ensure the security and integrity of data within these systems.
  • Data Engineer: Data engineers build and manage data infrastructure, develop ETL (Extract, Transform, Load) processes to prepare data for analysis, and collaborate closely with data scientists and analysts to ensure the availability and quality of data.

Tools Used for Data Science

  • Python: A versatile programming language widely used for data analysis, machine learning, and scientific computing due to its rich ecosystem of libraries like NumPy, Pandas, and Scikit-learn.
  • R: A programming language and environment specifically designed for statistical analysis and visualization, commonly used in academia and research for data analysis tasks.
  • Jupyter Notebook: An open-source web application that allows users to create and share documents containing live code, equations, visualizations, and narrative text, making it an ideal tool for interactive data analysis and exploration.
  • SQL: Structured Query Language (SQL) is essential for working with relational databases, allowing data scientists to query, manipulate, and manage data stored in databases efficiently.
  • TensorFlow: An open-source machine learning framework developed by Google for building and training deep learning models, widely used for tasks like image classification, natural language processing, and reinforcement learning.
  • Scikit-learn: A simple and efficient library for machine learning in Python, providing tools for data preprocessing, model selection, and evaluation, making it suitable for both beginners and experienced data scientists.
  • Apache Spark: A fast and general-purpose cluster computing system for big data processing, offering APIs in Java, Scala, Python, and R, commonly used for large-scale data processing, machine learning, and stream processing tasks.
  • Tableau: A powerful data visualization tool that allows users to create interactive and shareable dashboards, reports, and visualizations, enabling data scientists to communicate their findings effectively to stakeholders.
  • Docker: A containerization platform that allows developers to package and distribute applications and their dependencies in isolated environments, making it easier to deploy and manage data science projects across different environments.
  • Git: A distributed version control system used for tracking changes in source code during software development, essential for collaboration and version management in data science projects.

Organizational Benefits of the Data Science

  • Data-Driven Decision Making: Equipping employees with data science skills enables organizations to make informed decisions based on data analysis, leading to improved efficiency and effectiveness in various business processes.
  • Increased Competitiveness: By leveraging data science techniques, organizations can gain insights into market trends, customer behavior, and competitor strategies, allowing them to stay ahead of the competition and seize new opportunities.
  • Improved Productivity: Data science empowers employees to automate repetitive tasks, streamline processes, and optimize workflows, leading to increased productivity and resource utilization across the organization.
  • Enhanced Customer Experience: By analyzing customer data, organizations can personalize products, services, and marketing campaigns to better meet the needs and preferences of their target audience, leading to higher customer satisfaction and loyalty.
  • Cost Reduction: Data science enables organizations to identify inefficiencies, eliminate waste, and optimize resource allocation, resulting in cost savings and improved financial performance.
  • Risk Management: Data science techniques such as predictive analytics help organizations identify and mitigate risks proactively, whether in financial investments, supply chain management, or cybersecurity, reducing potential losses and liabilities.
  • Innovation and Growth: Data science fosters innovation by uncovering insights, patterns, and trends that can lead to the development of new products, services, and business models, driving growth and market expansion.
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Key Features

ACTE Hyderabad offers Data Science 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.


Syllabus of Data Science Course in Bangalore
Module 1: Data Science Basics
  • Introduction to Data Science
  • Significance of Data Science
  • R Programming basics
Module 2: Python Fundamentals
  • Python Introduction
  • Indentations in Python
  • Python data types and operators
  • Python Functions
Module 3: Data Structures and Data Manipulation
  • Data Structures Overview
  • Identifying the Data Structures
  • Allocating values to the Data Structures
  • Data Manipulation Significance
  • Dplyr Package and performing different data manipulation operations
Module 4: Data visualization
  • Introduction to Data Visualisation
  • Various kinds of graphs, Graphics grammar
  • Ggplot2 package
  • Multivariant analysis by using geom_boxplot
  • Univariant analysis
  • Histogram, barplot, multivariate distribution, and density plot
  • Bar plots for the categorical variables through geop_bar() and the theme() layer
Module 5: Statistics
  • Statistics Importance
  • Statistics classification, Statistical terminology
  • Data types, Probability types, measures of speed, and central tendency
  • Covariance and Correlation, Binary and Normal distribution
  • Data Sampling, Confidence, and Significance levels
  • Hypothesis Test and Parametric testing
Module 6: Introduction to Machine Learning
  • Machine Learning Fundamentals
  • Supervised Learning, Classification in Supervised Learning
  • Linear Regression and mathematical concepts related to linear regression
  • Classification Algorithms, Ensemble Learning techniques
Module 7: Logistic Regression
  • Logistic Regression Introduction
  • Logistic vs Linear Regression, Poisson Regression
  • Bivariate Logistic Regression, math related to logistic regression
  • Multivariate Logistic Regression
  • Building Logistic Models
  • False and true positive rate
  • Real-time applications of Logistic Regression
Module 8: Random Forest and Decision Trees
  • Classification Techniques
  • Decision Tree Induction Algorithm
  • Implementation of Random Forest in R
  • Differences between classification tree and regression tree
  • Naive Bayes, SVM
  • Entropy, Gini Index, Information Gain
Module 9: Unsupervised learning
  • Clustering, K-means clustering, Canopy Clustering, and Hierarchical Clustering
  • Unsupervised learning, Clustering algorithm, K-means clustering algorithm
  • K-means theoretical concepts, k-means process flow, and K-means implementation
  • Implementing Historical Clustering in R
  • PCA(Principal Component Analysis) Implementation in R
Module 10: Denial-of-Service
  • DoS/DDoS Concepts
  • Botnets
  • DoS/DDoS Attack Techniques
  • DDoS Case Study
  • DoS/DDoS Countermeasures
Module 11: Natural Language Processing
  • Natural language processing and Text mining basics
  • Significance and use-cases of text mining
  • NPL working with text mining, Language Toolkit(NLTK)
  • Text Mining: pre-processing, text-classification and cleaning
Module 12: Mathematics for Data Science
  • Numpy Basics
  • Numpy Mathematical Functions
  • Probability Basics and Notation
  • Correlation and Regression
  • Joint Probabilities
  • Bayes Theorem
  • Conditional Probability, sum rule, and product rule
Module 13: Scientific Computing through Scipy
  • Scipy Introduction and characteristics
  • Integrate, Cluster, Signal, Fftpack, and Bayes Theorem
Module 14: Python Integration with Spark
  • Pyspark basics
  • Uses and Need of pyspark
  • Pyspark installation
  • Advantages of pyspark over MapReduce
  • Pyspark applications
Module 15: Deep Learning and Artificial Intelligence
  • Machine Learning effect on Artificial Intelligence
  • Deep Learning Basics, Working of Deep Learning
  • Regression and Classification in the Supervised Learning
  • Association and Clustering in unsupervised learning
  • Basics of Artificial Intelligence and Neural Networks
  • Supervised Learning in Neural Networks, multi-layer network
  • Deep Neural Networks, Convolutional Neural Networks
  • Reinforcement Learning
  • Recurrent Neural Networks, Deep learning graphics processing unit
  • Deep Learning Applications, Time series modeling
Module 16: Keras and TensorFlow API
  • Tensorflow Basics and Tensorflow open-source libraries
  • Deep Learning Models and Tensor Processing Unit(TPU)
  • Graph Visualisation, keras
  • Keras neural-network
  • Define and Composing multi-complex output models through Keras
  • Batch normalization, Functional and Sequential composition
  • Implementing Keras with tensorboard
  • Implementing neural networks through TensorFlow API
Module 17: Restricted Boltzmann Machine and Autoencoders
  • Basics of Autoencoders and rbm
  • Implementing RBM for the deep neural networks
  • Autoencoders features and applications
Module 18: Big Data Hadoop and Spark
  • Big Data and Hadoop Basics
  • Hadoop Architecture, HDFS
  • MapReduce Framework and Pig
  • Hive and HBase
  • Basics of Scala and Functional Programming
  • Kafka basics, Kafka Architecture
  • Kafka cluster and Integrating Kafka with Flume
  • Introduction to Spark
  • Spark RDD Operations, writing spark programs
  • Spark Transformations, Spark streaming introduction
  • Spark streaming Architecture, Spark Streaming Features
  • Structured streaming Architecture, Dstreams, and Spark Graphx
Module 19: Tableau
  • Data Visualisation Basics
  • Data Visualisation Applications
  • Tableau Installation and Interface
  • Tableau Data Types, Data Preparation
  • Tableau Architecture
  • Getting Started with Tableau
  • Creating sets, Metadata and Data Blending
  • Arranging visual and data analytics
  • Mapping, Expressions, and Calculations
  • Parameters and Tableau prep
  • Stories, Dashboards, and Filters
  • Graphs, charts
  • Integrating Tableau with Hadoop and R
Module 20: MongoDB
  • MongoDB and NoSQL Basics
  • MongoDB Installation
  • Significance of NoSQL
  • CRUD Operations
  • Data Modeling and Management
  • Data Indexing and Administration
  • Data Aggregation Schema
  • MongoDB Security
  • Collaborating with Unstructured Data
Module 21: SAS Basics
  • SAS Enterprise Guide
  • SAS functions and Operators
  • SAS Data Sets compilation and creation
  • SAS Procedures
  • SAS Graphs
  • SAS Macros
  • Advance SAS
Module 22: MS Excel
  • Entering Data
  • Logical Functions
  • Conditional Formatting
  • Validation, Excel formulas
  • Data sorting, Data Filtering, Pivot Tables
  • Creating charts, Charting techniques
  • File and Data security in excel
  • VBA macros, VBA IF condition, and VBA loops
  • VBA IF condition, For loop
  • VBA Debugging and Messaging
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Get Hands-on Knowledge about Real-Time Data Science Projects

Project 1
Predictive Maintenance

Predict equipment failures, optimize maintenance in manufacturing with ML.

Project 2
Customer Segmentation

Use clustering for personalized marketing and improved customer engagement.

Get Hired Quickly With Our Data Science Course Placement:

  • Begin your Data Science adventure with our professional mentors, who will provide individualized guidance based on your needs and goals. Our specialized staff will provide you with useful insights and support as you begin on your journey to learn Data Science.
  • Our Data Science placement ensures you to receive expert assistance in problem-solving, code reviews, and career guidance, empowering you to navigate the dynamic landscape of data analysis with confidence.
  • Enhance your confidence with customized guidance on technical interviews, behavioral assessments, and mock interviews tailored to Data Science-related roles.
  • To stand out in the competitive employment market, create compelling resumes that highlight your Data Science placement expertise and project successes. To boost your candidacy, showcase your skills with accuracy, focusing on project successes.
  • Gain access to unique Data Science opportunities with leading organizations like Google, Amazon, and Microsoft, among others. Our curriculum will provide you with the skills and knowledge required to flourish in the competitive profession of Data Science, opening the door to lucrative employment opportunities.
  • We nurture professional development through job expos, industry seminars, and networking events, connecting Data Science enthusiasts with industry leaders for valuable insights and opportunities.
  • Enhance your soft skills, including teamwork, communication, and presentation abilities, through our comprehensive training, essential for excelling in a Data Science career.

Advance Your Career With Our Data Science Certification

Our Data Science certification is globally recognized and esteemed by organizations worldwide. We cater to recent graduates, aspiring learners, and seasoned professionals seeking to enhance their skills. Renowned for its accreditation, the Data Science Certification significantly boosts the credibility of your resume, elevating your prospects of securing prestigious positions with leading organizations globally. To earn this esteemed certification, completion of hands-on training and assignments is mandatory, ensuring proficiency in practical application.

Yes, achieving a Data Science certification can result in salary growth over time. It validates expertise, showcases commitment to professional development, and enhances competitiveness in salary negotiations.

Data Science certification validates skills and expertise, enhancing employability and credibility. It demonstrates proficiency in Data Science practices and tools, opening doors to lucrative career opportunities.

Yes it is highly beneficial:
  • Data Scientist
  • Machine Learning Engineer
  • Data Analyst
  • Business Intelligence Analyst
  • Big Data Engineer
  • AI Research Scientist
  • Increased job prospects
  • Demonstrated proficiency in Data Science
  • Enhanced credibility in the industry
  • Opportunities for career advancement
  • Potential for higher salary earnings

Yes, obtaining a Data Science course certification significantly increases your chances of securing employment by validating essential skills and expertise. Certified individuals become highly desirable to employers in today's competitive job market, positioning them as top candidates for exciting career opportunities.

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.

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Embark on Your Journey with Our Expert Data Science Trainers

  • Our Data Science course boasts experienced trainers with a minimum of 7+ years of practical industry experience in Data Science methodologies, holding key positions in leading organizations.
  • Receive comprehensive guidance from our Data Science trainers, covering foundational to advanced concepts, ensuring a strong understanding of Data Science principles and techniques.
  • Our Data Science Trainers bring a wealth of expertise from renowned IT companies such as Accenture, IBM, Google, and Amazon, integrating real-world insights into the learning process.
  • Participate in an interactive learning environment where questions are encouraged, and our seasoned trainers provide continuous support and guidance throughout your Data Science training.
  • Our skilled educators will keep you up to date on the newest breakthroughs in Data Science by exposing you to cutting-edge approaches and industry best practices.
  • Benefit from tailored assistance, clear explanations of intricate subjects, and engaging course materials designed to enhance your learning journey and achieve optimal results in your Data Science endeavors.

Data Science Course FAQs

Looking for better Discount Price?

Call now: +91 93833 99991 and know the exciting offers available for you!
  • ACTE is the Legend in offering placement to the students. Please visit our Placed Students List on our website
  • We have strong relationship with over 700+ Top MNCs like SAP, Oracle, Amazon, HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc.
  • More than 3500+ students placed in last year in India & Globally
  • ACTE conducts development sessions including mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
  • 85% percent placement record
  • Our Placement Cell support you till you get placed in better MNC
  • Please Visit Your Student Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
ACTE gives Certificate For Completing A Course
  • Certification is Accredited by all major Global Companies
  • ACTE is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS and National Institute of Education (NIE) Singapore
  • The entire Data Science training has been built around Real Time Implementation
  • You Get Hands-on Experience with Industry Projects, Hackathons & lab sessions which will help you to Build your Project Portfolio
  • GitHub repository and Showcase to Recruiters in Interviews & Get Placed
All the instructors at ACTE are practitioners from the Industry with minimum 9-12 yrs of relevant IT experience. They are subject matter experts and are trained by ACTE for providing an awesome learning experience.
No worries. ACTE assure that no one misses single lectures topics. We will reschedule the classes as per your convenience within the stipulated course duration with all such possibilities. If required you can even attend that topic with any other batches.
We offer this course in “Class Room, One to One Training, Fast Track, Customized Training & Online Training” mode. Through this way you won’t mess anything in your real-life schedule.

Why Should I Learn Data Science Course At ACTE?

  • Data Science Course in ACTE is designed & conducted by Data Science experts with 10+ years of experience in the Data Science domain
  • Only institution in India with the right blend of theory & practical sessions
  • In-depth Course coverage for 60+ Hours
  • More than 50,000+ students trust ACTE
  • Affordable fees keeping students and IT working professionals in mind
  • Course timings designed to suit working professionals and students
  • Interview tips and training
  • Resume building support
  • Real-time projects and case studies
Yes We Provide Lifetime Access for Student’s Portal Study Materials, Videos & Top MNC Interview Question.
You will receive ACTE globally recognized course completion certification Along with National Institute of Education (NIE), Singapore.
We have been in the training field for close to a decade now. We set up our operations in the year 2009 by a group of IT veterans to offer world class IT training & we have trained over 50,000+ aspirants to well-employed IT professionals in various IT companies.
We at ACTE believe in giving individual attention to students so that they will be in a position to clarify all the doubts that arise in complex and difficult topics. Therefore, we restrict the size of each Data Science batch to 5 or 6 members
Our courseware is designed to give a hands-on approach to the students in Data Science. The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.
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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      Job Opportunities in Data Science

      More Than 35% Of Developers Prefer Data Science. Data Science Is The Most Popular And In-Demand Programming Language In The Tech World.

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