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Apache Spark Training in Pune

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Rated #1 Recoginized as the No.1 Institute for Apache Spark Training in Pune

Enhance your expertise with professional Apache Spark Training in Pune. Master the latest Apache Spark techniques and become proficient in big data processing, real-time analytics, and machine learning.

This Apache Spark Training Course is designed for professionals looking to excel in data engineering, data science, and big data analytics using Apache Spark. Learn to design, implement, and optimize Spark applications while addressing real-world challenges, boosting your skills in this high-demand field.

Master key Apache Spark concepts to advance your career.
Gain practical experience with real-world Apache Spark projects.
Take Apache Spark Training in Pune to elevate your big data skills.
Access affordable, industry-recognized training with placement support.
Unlock career opportunities with top IT, data, and enterprise companies.
Join over 16,854 professionals trained in advanced Apache Spark techniques.

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Fee INR 18000
INR 14000

Training

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Case Studies and Projects 8+
Hours of Training 45+
Placement Assurance 100%
Expert Support 24/7
Support & Access Lifetime
Certification Yes
Skill Level All
Language All

Boost Your Career With Apache Spark Course

We offer guidance and mentorship to help you leverage your Apache Spark skills effectively in the gig economy or as a business venture.
Regular skill assessments and mock exams will gauge your progress and readiness for certification. These practice tests are designed to give you the confidence to excel in the final certification exam.
Practice your Apache Spark skills on cloud-based labs that provide a safe and flexible environment for hands-on learning.
Our curriculum is thoughtfully designed by industry experts to align with current market demands and job requirements.
No need to worry about setting up complex infrastructure; focus on learning and experimenting with ease.
Stay up-to-date with the latest developments in Apache Spark and emerge as a sought-after professional.
Resume and Interview Preparation Support, including Concepts like Spark and Hadoop, Introduction to Scala, SPARK Environment, SCALA Environment, Deep Dive into Scala, Traits and Mixins, Pattern Matching, Deep Dive into Spark, Parallel Programming, and Spark EcoSystem.

Classroom Batch Training
One To One Training
Online Training
Customized Training
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Other Categories Placements

Non-IT to IT (Career Transition) 2371+
Diploma Candidates3001+
Non-Engineering Students (Arts & Science)3419+
Engineering Students3571+
CTC Greater than 5 LPA4542+
Academic Percentage Less than 60%5583+
Career Break / Gap Students2588+

Top Placement Record

28-Apr-2025

Mon-Fri

Weekdays Regular

08:00 AM & 10:00 AM Batches

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

30-Apr-2025

Mon-Fri

Weekdays Regular

08:00 AM & 10:00 AM Batches

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

03-May-2025

Sat,Sun

Weekend Regular

(10:00 AM - 01:30 PM)

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

04-May-2025

Sat,Sun

Weekend Fasttrack

(09:00 AM - 02:00 PM)

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

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Most Jobs Oriented Tools Covered in Apache Spark

Course Objectives

What are the benefits of Apache Spark training for professionals?

Professionals should take Apache Spark training because it increases employment chances in data analytics and related sectors and offers skills in sophisticated data processing, scalability, integration with the big data ecosystem, and machine learning capabilities.

Why should I enroll Apache Spark training?

Professionals that complete Apache Spark training get enhanced data processing abilities
scalability
Integration with the big data ecosystem
Machine learning capabilities
Improving their job prospects and encouraging innovation in the data analytics industry.

Which industries need professionals with Apache Spark skills?

The IT services
Software development
E-commerce
Financial
Telecommunications sectors in Pune place a high value on Apache Spark expertise.

Can individuals with no prior programming experience benefit from Apache Spark training?

Yes, individuals with no prior programming experience can benefit from Apache Spark training as it provides a structured learning path, hands-on exercises, and practical examples that gradually build programming skills. The training enables them to acquire foundational knowledge and develop proficiency in using Apache Spark for data processing and analytics, opening doors to exciting career opportunities in the field.

Are there any job placement assistance associated with Apache Spark Program?

Resume building
Interview preparation
Connecting students with potential employers in the industry

What are the prerequisites for Apache Spark training enrollment?

While not mandatory, familiarity with programming concepts and basic knowledge of languages like Python or Scala can be beneficial for individuals interested in Apache Spark training. A basic understanding of big data concepts and experience with SQL may also be helpful for effective learning and application of Spark's capabilities.

Mention some tools that are taught in Apache Spark course?

Spark Core for distributed data processing and computation
Spark SQL for working with structured data using SQL queries and DataFrame API.
Other tools may include Spark Streaming for real-time data processing, MLlib for machine learning, and GraphX for graph processing.

Is there a certification upon completing the Apache Spark training?

Yes, upon completion of an Apache Spark training program, participants can often earn a certification that validates their knowledge and skills in Apache Spark.
This certification can enhance their credibility in the job market and demonstrate their proficiency in using Spark for data processing and analytics.

What topics are covered in the Apache Spark course curriculum?

Spark and Hadoop platform
Introduction to Scala
SPARK Environment
SCALA Environment
Traits and Mixins
Pattern Matching
Spark EcoSystem

How is Apache spark training different from other similar programs?

This training program differentiates itself from others in Pune by offering a comprehensive curriculum designed by industry experts, hands-on learning in Apache Spark, and lifetime access to a student portal with study materials, videos, and interview preparation resources, ensuring a holistic learning experience and strong career readiness.

What is the scope of Apache Spark in the future?

The future scope of Apache Spark is promising as it continues to be widely adopted in industries for big data processing, real-time analytics, and machine learning due to its scalability, performance, and integration capabilities, making it a crucial technology for organizations leveraging data-driven decision-making and advanced analytics.

Apache Spark: Master Big Data Processing

Discover the robust features of Apache Spark, a flexible data processing platform created for the effective management of large-scale data. Apache Spark is the best tool for managing large datasets because of its capacity to quickly complete difficult processing jobs. Using it alone or in conjunction with other distributed computing technologies, it provides the freedom to divide data processing responsibilities across several machines. Begin your educational journey with us at ACTE, where we provide thorough online and classroom training for Apache Spark tutorial. Unlock the possibilities of this cutting-edge data processing technology by gaining practical experience.

Additional Info

Apache Spark: The Next Big Data Technology

The big data industry is undergoing a revolution because to Apache Spark's robust capabilities and flexible features. Spark, a state-of-the-art data processing platform, is positioned to influence the direction of big data analytics. Large datasets may be processed quite quickly, and the flexibility to split up data processing duties across several processors allows for scalability and effective computing. Spark is a popular option for addressing a variety of big data difficulties because to its robust ecosystem and support for several data processing tasks, including streaming, machine learning, and graph processing. Apache Spark is advancing big data analytics with its ongoing development and innovation, and it has enormous potential to influence the direction of data-driven insights and decision-making in the future.

A Practical Approach to Iterative Algorithms:

Apache Spark enables efficient handling of iterative algorithms through "iterative computation" or "iterative processing."
The Resilient Distributed Datasets (RDDs) abstraction in Spark allows iterative algorithms to run in a distributed and fault-tolerant manner.
RDDs store data in memory across multiple iterations, reducing serialization and disk I/O overhead for improved performance.
Spark's "caching" feature stores intermediate data in memory, speeding up subsequent iterations by reusing computed results.
Iterative processing in Spark optimizes algorithms that require multiple iterations over large datasets.
The caching mechanism in Spark prevents unnecessary data re-computation, enhancing iterative computation speed.
High-level machine learning libraries like Spark MLlib provide optimized implementations of popular iterative algorithms.
Spark MLlib includes algorithms like logistic regression, collaborative filtering, and k-means clustering.
These libraries leverage Spark's distributed computing capabilities for scalable and faster execution.
Overall, Apache Spark's iterative processing features and machine learning libraries offer an efficient and scalable framework for handling iterative algorithms on large datasets.

The Process Made So Simple by Apache Spark:

With the help of many essential characteristics that make it simple to use and very effective, Apache Spark streamlines and simplifies dealing with massive data:

Apache Spark Programming: Apache Spark offers a single programming API that may be used for a variety of data processing activities, including batch processing, streaming, machine learning, and graph processing. Regardless of the precise job at hand, this uniform API lowers the learning curve and enables developers to create code in a familiar way.
In-Memory Processing: Spark uses in-memory computing to keep data in memory, making data access and processing much faster than they would be on a disk-based system. As a result of this feature's elimination of repetitive I/O operations, execution times are sped up and overall performance is enhanced.
Spark Parallel: It enables parallel processing by distributing data and computation over a cluster of computers. It is simple to scale up processing power as necessary since it automatically splits and distributes data among cluster nodes. With the help of this distributed computing paradigm, Spark is able to handle enormous datasets and carry out calculations very quickly.
High-Level Libraries: For typical data processing tasks, Spark provides high-level libraries, such as Spark SQL for structured data processing, Spark Streaming for real-time data processing, Spark MLlib for machine learning, and Spark GraphX for graph processing. These libraries offer pre-built functionality and optimised algorithms, simplifying the performance of complicated processes without requiring extensive custom implementation.
Spark Shell: Spark offers a user-friendly interactive shell (Spark Shell) that enables interactive data exploration and experimentation. It is simple to test concepts and draw conclusions from the data in this interactive environment since it supports rapid prototyping, iterative development, and ad-hoc analysis.
Community & Ecosystem: The ecosystem of tools, frameworks, and connectors for Apache Spark is diverse and flourishing. Improvements, bug fixes, and new features are continuously added as a consequence of this community-driven development. The ecosystem allows for easy and flexible integration with current systems by supporting a variety of data sources, data formats, cloud platforms, and third-party solutions.

Top Companies Using Apache Spark:

Amazon Web Services (AWS): On its cloud platform, AWS provides the Amazon EMR (Elastic MapReduce) service, which makes use of Apache Spark to handle massive data sets.
Databricks: Databricks offers a unified analytics platform that mainly relies on Spark for data processing, machine learning, and real-time analytics. Databricks was formed by the people who created Apache Spark.
Netflix: Netflix uses Apache Spark for analytics, content personalisation, and a variety of data processing jobs.
IBM: To allow scalable and effective big data processing and sophisticated analytics, IBM has integrated Apache Spark into its data analytics platform, IBM Watson.
Microsoft: Apache Spark is supported as a processing engine by Microsoft Azure HDInsight, a cloud-based big data analytics platform, enabling customers to take use of Spark's capabilities for data processing and analytics.
Intel: To improve their products and services, Intel leverages Apache Spark for massive Big Data Analytics Courses data analytics, machine learning, and real-time stream processing.
Adobe: To obtain insights and improve user experiences across their range of creative and marketing products, Adobe uses Apache Spark for data processing, analytics, and machine learning jobs.
Uber: For a variety of data processing andReal-time analytics application cases include fraud detection analytics, and demand forecasting, Uber makes use of Apache Spark.
LinkedIn: LinkedIn utilises Apache Spark for a variety of data-driven applications, such as fraud detection, content analysis, and personalised recommendations.
Salesforce: To improve its customer relationship management (CRM) platform and provide data-driven insights, Salesforce uses Apache Spark for data processing, analytics, and machine learning operations.

Apache Spark Ecosystem: Understanding the Components and Tools

Apache Spark Core: This is the foundation of the Spark ecosystem. It provides the distributed task scheduling, memory management, and fault tolerance capabilities that power all other Spark components.
Spark SQL: Spark SQL is a module in Apache Spark that provides a programming interface and optimized execution engine for querying structured and semi-structured data using SQL-like syntax. It enables seamless integration between relational and procedural processing.
Spark Streaming: Spark Streaming enables processing and analyzing real-time streaming data, making it suitable for applications like log analysis, fraud detection, and sentiment analysis. It ingests and processes data in mini-batches, allowing near-real-time analysis.
Spark MLlib: MLlib is Spark's machine learning library that offers a wide range of distributed machine learning algorithms and utilities. It simplifies the development of scalable machine learning pipelines, including feature extraction, model training, and evaluation.
Spark GraphX: Spark GraphX is a graph processing library that provides high-level APIs for graph computation and analytics. It allows users to perform graph-based operations such as graph traversal, motif finding, and graph algorithms like PageRank and connected components.
SparkR: SparkR is an R package that allows R users to interact with Spark, enabling them to leverage Spark's distributed computing capabilities from the R programming environment. It enables seamless integration between R and Spark data processing workflows.
Apache Zeppelin: Zeppelin is a web-based notebook that offers a collaborative, interactive environment for data exploration. It is practical for using Spark since it supports several programming languages, including Scala, Python, SQL, and R.
Apache Hive: Hive is a Hadoop Distributed File System (HDFS)-based data warehouse architecture that offers a SQL-like interface for querying and managing big datasets. Data processing between the two systems is simple because to its integration with Spark SQL.
Apache Kafka: Spark Streaming is frequently used in combination with Kafka, a distributed streaming platform. It is a popular option for real-time data input in Spark applications because it enables high-throughput, fault-tolerant streaming of data from multiple sources.

Key Features

ACTE Pune offers Apache Spark 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 .

Curriculum

Syllabus of Apache Spark Training in Pune

Module 1: Introduction to Spark

Introduction to Spark
Spark overcomes the drawbacks of working on MapReduce
Understanding in-memory MapReduce
Interactive operations on MapReduce
Spark stack, fine vs. coarse-grained update, Spark Hadoop YARN, HDFS Revision, and YARN Revision
The overview of Spark and how it is better than Hadoop
Deploying Spark without Hadoop
Spark history server and Cloudera distribution

Module 2: Spark Basics

Spark installation guide
Spark configuration
Memory management
Executor memory vs. driver memory
Working with Spark Shell
The concept of resilient distributed datasets (RDD)
Learning to do functional programming in Spark
The architecture of Spark

Module 3: Working with RDDs in Spark

Spark RDD
Creating RDDs
RDD partitioning
Operations and transformation in RDD
Deep dive into Spark RDDs
The RDD general operations
Read-only partitioned collection of records
Using the concept of RDD for faster and efficient data processing
RDD action for the collect, count, collects map, save-as-text-files, and pair RDD functions

Module 4: Aggregating Data with Pair RDDs

Understanding the concept of key-value pair in RDDs
Learning how Spark makes MapReduce operations faster
Various operations of RDD
MapReduce interactive operations
Fine and coarse-grained update
Spark stack

Module 5: Writing and Deploying Spark Applications

Comparing the Spark applications with Spark Shell
Creating a Spark application using Scala or Java
Deploying a Spark application
Scala built application
Creation of the mutable list, set and set operations, list, tuple, and concatenating list
Creating an application using SBT
Deploying an application using Maven
The web user interface of Spark application
A real-world example of Spark
Configuring of Spark

Module 6: Parallel Processing

Learning about Spark parallel processing
Deploying on a cluster
Introduction to Spark partitions
File-based partitioning of RDDs
Understanding of HDFS and data locality
Mastering the technique of parallel operations
Comparing repartition and coalesce
RDD actions

Module 7: Spark RDD Persistence

The execution flow in Spark
Understanding the RDD persistence overview
Spark execution flow, and Spark terminology
Distribution shared memory vs RDD
RDD limitations
Spark shell arguments
Distributed persistence
RDD lineage
Key-value pair for sorting implicit conversions like CountByKey, ReduceByKey, SortByKey, and AggregateByKey

Module 8: Spark MLlib

Introduction to Machine Learning
Types of Machine Learning
Introduction to MLlib
Various ML algorithms supported by MLlib
Linear regression, logistic regression, decision tree, random forest, and K-means clustering techniques

Module 9: Integrating Apache Flume and Apache Kafka

Why Kafka and what is Kafka?
Kafka architecture
Kafka workflow
Configuring Kafka cluster
Operations
Kafka monitoring tools
Integrating Apache Flume and Apache Kafka

Module 10: Spark Streaming

Introduction to Spark Streaming
Features of Spark Streaming
Spark Streaming workflow
Initializing StreamingContext, discretized Streams (DStreams), input DStreams and Receivers
Transformations on DStreams, output operations on DStreams, windowed operators and why it is useful
Important windowed operators and stateful operators

Module 11: Improving Spark Performance

Introduction to various variables in Spark like shared variables and broadcast variables
Learning about accumulators
The common performance issues
Troubleshooting the performance problems

Module 12: Spark SQL and Data Frames

Learning about Spark SQL
The context of SQL in Spark for providing structured data processing
JSON support in Spark SQL
Working with XML data
Parquet files
Creating Hive context
Writing data frame to Hive
Reading JDBC files
Understanding the data frames in Spark
Creating Data Frames
Manual inferring of schema
Working with CSV files
Reading JDBC tables
Data frame to JDBC
User-defined functions in Spark SQL
Shared variables and accumulators
Learning to query and transform data in data frames
Data frame provides the benefit of both Spark RDD and Spark SQL
Deploying Hive on Spark as the execution engine

Module 13: Scheduling/Partitioning

Learning about the scheduling and partitioning in Spark
Hash partition
Range partition
Scheduling within and around applications
Static partitioning, dynamic sharing, and fair scheduling
Map partition with index, the Zip, and GroupByKey
Spark master high availability, standby masters with ZooKeeper
Single-node recovery with the local file system and high order functions

Show Less

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Hands-on Real Time Apache Spark Projects

Project 1

Real-time Twitter Sentiment Analysis

Analyze and visualize the sentiments of live Twitter feeds using Apache Spark's streaming capabilities.

Project 2

Movie Recommendation System

Build a collaborative filtering-based recommendation system with Spark's MLlib for personalized movie suggestions.

This is How ACTE Students Prepare for Better Jobs

Internship and Practical Experience

Gain invaluable hands-on experience through our internship program, where theoretical knowledge meets practical application. Elevate your skills, expand your network, and pave the way for a successful career journey.

Hands On Projects

Experienced in leading hands-on projects, applying technical skills to drive successful outcomes. Proficient in project management and collaboration to ensure effective execution and delivery.

Resume Preparation

Expertise in developing standout resumes that effectively showcase your skills, experience, and achievements, maximizing your chances of securing interviews and advancing your career goals.

Apptitude and Technical skills

Develop your aptitude and technical prowess with our comprehensive training programs. Master essential skills, stay ahead of industry trends, and unlock new opportunities for professional growth and success.

Mock Interview

Hone your interview skills with our realistic mock interview sessions tailored to your desired role. Gain confidence, refine your responses, and secure your dream job.

Group Discussion

Engage in dynamic group discussions to enhance communication, teamwork, and critical thinking skills. Cultivate confidence and articulate your ideas effectively in a collaborative setting.

Until You Get a Job in Top MNC

Persevere until you secure a position in a top-tier MNC, where your expertise is valued, and your career aspirations are fulfilled. Stay focused, determined, and relentless in your pursuit of success.

Employee Referal Program

Empower your network by referring talented individuals to join our team, and reap rewards through our Employee Referral Program. Together, let's build a stronger workforce and create opportunities for growth and success.

Apache Spark Training with Placement: Master Data Analytics

ACTE Pune provides placement opportunities as an add-on benefit to every student or professional who completes our classroom or online training.

Our association with top organizations like HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM, and more enables us to place our students in leading MNCs worldwide.
Our dedicated student portal provides access to interview schedules and timely email notifications, keeping students informed about placement opportunities.
Upon completing 70% of the Apache Spark training, we arrange interview calls and prepare students for face-to-face interactions with prospective employers.
Our Apache Spark training assist students in creating resumes that align with current industry requirements, maximizing their chances of securing desirable positions.
With a dedicated placement support team, we provide personalized assistance to students in securing placements based on their preferences and career goals.
We conduct mock exams and interviews to assess the knowledge gaps of candidates, helping them identify areas for improvement and enhance their interview performance.

Apache Spark Certification: Master Data Processing & Analytics

ACTE's certification, including the Apache Spark certification, holds global accreditation and is recognized by major companies worldwide. Upon completion of our comprehensive theoretical and practical training, both fresher's and corporate trainees receive a valuable certification that enhances their resumes and opens doors to prominent job positions in leading MNCs globally. This certification is awarded only after successfully completing our rigorous training program and practical-based projects.

What is Apache Spark certification?

Apache Spark certification validates the expertise and proficiency of individuals in utilizing Apache Spark for data processing, analytics, and machine learning. It serves as a recognized credential that demonstrates the ability to effectively leverage Spark's capabilities in real-world scenarios, enhancing career opportunities in the field of big data analytics.

Why should someone consider getting certified in Apache Spark?

Getting certified in Apache Spark is beneficial as it validates your skills and expertise in utilizing Spark for data processing and analytics, enhancing your credibility in the job market.
It opens up new career opportunities and demonstrates your commitment to continuous learning and professional growth in the field of big data analytics.

Are there different levels or types of Apache Spark certifications?

Yes, Apache Spark certifications are available at different levels and types.

The certifications typically include beginner, intermediate, and advanced levels, allowing individuals to demonstrate their proficiency in various aspects of Apache Spark, such as data processing, analytics, machine learning, and optimization.

What are the benefits of having an Apache Spark certification?

Having an Apache Spark certification provides several benefits, including enhanced career prospects, increased job opportunities in data processing and analytics roles, recognition of expertise in Apache Spark, and the ability to work on complex big data projects with confidence. It also validates your skills to employers and clients, boosting your professional credibility in the field.

Are there any prerequisites for the Apache Spark certification exam?

In general, persons planning to take the Apache Spark certification exam are advised to have a fundamental grasp of programming principles, familiarity with Apache Spark, and hands-on experience with Spark projects.

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Learn Apache Spark from Our Industry Experts

Our Apache Spark training is delivered by certified professionals with a minimum of 9+ years of experience in their respective domains.
Our trainers bring their industry expertise to the training sessions by incorporating real-life projects, providing practical exposure to learn Apache Spark concepts and applications.
Our trainers have affiliations with renowned companies such as Cognizant, Dell, Infosys, IBM, L&T InfoTech, TCS, HCL Technologies, etc., offering valuable insights into industry practices and requirements.
Trainers actively support candidates in securing placements through employee referrals and internal hiring processes within their respective companies.
Our trainers are not only industry experts but also subject specialists who have mastered the art of running applications, delivering the best Apache Spark training to students.
Our Apache Spark training in Pune has received prestigious awards from recognized IT organizations, validating our commitment to delivering high-quality training and industry-relevant skills.

Apache Spark Software Course FAQs

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Does ACTE provide placement?

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

Is ACTE certification good?

ACTE

Certificate

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

Work On Live Projects?

The entire Apache Spark Software 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

Who are the Trainers?

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.

What if I miss one (or) more class?

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.

What are the modes of training offered for this Apache Spark Software Course?

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 Apache Spark Software Course At ACTE?

Apache Spark Software Course in ACTE is designed & conducted by Apache Spark Software experts with 10+ years of experience in the Apache Spark Software 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

Can I Access the Course Material in Online?

Yes We Provide Lifetime Access for Student’s Portal Study Materials, Videos & Top MNC Interview Question.

What certification will I receive after course completion?

You will receive ACTE globally recognized course completion certification Along with project experience, job support, and lifetime resources.

How Old Is ACTE?

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.

What Will Be The Size Of A Apache Spark Software Batch At ACTE?

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 Apache Spark Software batch to 5 or 6 members

Will I Be Given Sufficient Practical Training In Apache Spark Software?

Our courseware is designed to give a hands-on approach to the students in Apache Spark Software. 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.

How Do I Enroll For The Apache Spark Software Course At ACTE?

You can contact our support number at +91 76691 00251 / Directly can do by ACTE.in's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India

Course Syllabus