Data Scientist/Engineer - Junior

Hello,

We appreciate you showing interest in our Job placement program. This program is a fee-based program wherein you pay partial fees before enrolling and the remainder fees (Payable in installments over 2 years) once you secure a Job which pays you a minimum salary of $75,000 P.A. or more.

I am attaching the Presentation with this email which explains everything about our program, includes some videos about SynergisticIT and events etc.

which we attend for connecting with the tech industry, cost of the program and technologies covered in the program and the methodology.

Once you have gone through the presentation please reply and let me know your interest in pursuing the program via email, text at 510-347-8118.

After that we will have a phone call to discuss and evaluate your suitability for our program.

If you feel the program is expensive you are 100% correct. However, it's because of the nature of our program.

I can go over the details over a call if you are interested in the program and are comfortable with the investment in the program.

Please do understand the final decision about the suitability of your candidature for our program will be made by my manager via a zoom call which will involve a discussion about your experience, skill set, personality, attitude and communication skills and ability to commit to the program.

FULL-TIME JOB PLACEMENT PROGRAM(REMOTE / FULL-TIME) :

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 :

Kindly go through the course contents in each of these technologies : -

1) 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.

Feel free to take a free 5-minute java test : -

2) Data Science / Machine learning 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.

XGboost, Hierarchical clustering, Polynomial Regression

Regards,