Junior Data Analyst/Engineer

Full-Time Job Placement Program

Under this program, we will make you stand out from the rest of the jobseekers by offering skill enhancement training on the technologies in-demand including time management skills, study skills, test-taking skills, and learning strategies after which we can assist candidates in getting jobs as software programmers, Java Programmers, Data scientists, Machine learning engineers, Data analysts. Herein we first give real-time hands-on experience on the technologies by the experts working in the industry(6-7 trainers), get candidates certified with IT Certifications given by Microsoft, Oracle, Amazon, IBM, Udemy like AWS/JAVA/SQL/TABLEAU/POWER BI/SAAS/EXCEL(Sessions to be attended separately), gives real-time projects to practice the technologies and get professional-level experience in the real-world scenario, prepare candidates for all types of Coding/Interview assessments, behavioral questions, and finally market and arrange the interviews(unlimited) for the FULL-TIME positions until they get an offer with our Fortune-500 technology clients on their direct payroll(W2 – NO CONTRACTS, NO SALARY CUTS).

We offer 2 tracks:

• Java Track | SynergisticIT
• Data Science Track | SynergisticIT

Java Track:

In the Java track, we will cover JAVA, AWS, MERN STACK, HADOOP. JAVA PROGRAM teaches you from scratch and requires no coding experience from learners. You'll be given an introduction to JAVA and OOPS and its related technologies like SERVLET, JSP, JQUERY, HIBERNATE, SPRING, JAVASCRIPT, and MICROSERVICES. Introduction to Java, Oops Concepts Multi-threading, Exception Handling, Java API's JSP, Servlets How to deploy a web application jQuery, AJAX, JavaScript, JSON, Jenkins, GitHub, Spring MVC, Spring Core, Spring Boot, Rest Webservices, Hibernate, Spring Security, Microservices. JPA, AOP in Spring, Spring IOC, REST API's, etc. MERN STACK will give you a better and in-depth understanding of CSS, HTML, JAVASCRIPT, MONGO DB, EXPRESS.JS, REACT, NODE.JS. Express. JS, React.JS, MongoDB using Mongoose, Bootstrap, Redux. PL/SQ/ORACLE and Databases Also Pl/SQL, stored procedures and triggers and databases like SQL, Oracle and Mysql and servers like Tomcat and J-boss. In HADOOP, you'll be given an introduction to BIG DATA, APACHE HADOOP, HADOOP ECOSYSTEM, CLOUDERA QUICKSTART VM along with core concepts of the Hadoop framework including MapReduce, HIVE, PIG, SQOOP, FLUME, HBASE, OOZIE. DATA STRUCTURES AND ALGORITHMS - Java programmers use data structures to store and organize data, and we use algorithms to manipulate the data in those structures. Data structures ex: Arrays, Linked List, Stacks, Queues Algorithms Examples: Breadth-First Search (BFS) Depth-First Search (Client) Insertion of a node in Linked List (On the basis of some constraints) Longest Common Subsequence Binary Search Find Minimum Depth of a Binary Tree AWS training includes all the fundamental concepts, infrastructure security, services of AWS like Amazon route, Amazon VPC, Elastic IP, Amazon EC2, Amazon RDS, AWS Direct connect. As programmers are supposed to be able to deploy their code to the cloud You learn AWS architecture, storage services, Content delivery, Compute services like AWS lambda, Beanstalk, AWS EC2, Auto scaling and load balancing.

Data Science Track:

Data science will have an introduction with PYTHON, further into numerical python, PANDAS DATA ANALYSIS, DATA VISUALISATION. Machine learning will cover everything from data science, Artificial intelligence, business analytics, deep learning, and computer science. Python will be covered along with Django and Scala in depth. PL/SQ/ORACLE and Databases AWS training includes all the fundamental concepts, infrastructure security, services of AWS like Amazon route, Amazon VPC, Elastic IP, Amazon EC2, Amazon RDS, AWS Direct connect. DATA STRUCTURES AND ALGORITHMS In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist. Our data science track covers most of the below: Topics and content might change based on the market requirements Python NumPy and Pandas Matplotlib data visualization Difference between Machine learning, Artificial Intelligence and Deep learning Data Manipulation: Cleansing-Munging Data Analysis. Statistics Tableau and Power BI PL/SQL and databases both SQL and NoSQL Data structures and algorithms Artificial Intelligence and Machine learning Machine learning Algorithms Decision Tree and Random Forest Algorithms Naïve Bayes and KNN Algorithm Support Vector Machine (SVM) Statistics Random variables, Zscore, Hypothesis testing, Expected Value Predictive Modeling : Different kind of Business problems and different phases of Predictive modeling and Popular Modeling Algorithms. Data exploration, Data preparation. Web scraping using Python Beautiful soup . What is web scraping (Difference between web scraping software vs a web browser), what is parser? Time series Analysis Different algorithms like Decision Tree and Random Forest algorithms, Support Vector Machine Algorithm Deep Learning and Computer vision Neural Networks, Tensor Flow and Keras Natural language processing (NLP) and Text mining Market Basket Analysis NLP with Python, Sentiment analysis Linear regression, Scikit Learn, Confusion matrix, Decision tree, Ensemble approach Random forest, Cross validation.