Master All the Essential Skills & Tools Used In Data Science, Analytics & Engineering Domain. Acquire a comprehensive and Hands-on Learning Experience with daily 1-1 Chat Support for Doubt Resolution and Career Advancement Techniques.
Enroll Now @ USD399
Get Complete Hands-on Practical Learning Experience through Assignments & Projects for Proper Confidence Building
Get unlimited access to course materials, resources, and updates for a lifetime.
Ideal for busy learners seeking a personalized and stress-free educational experience.
Get 1-1 Personal Chat Support for Doubt Clearance everyday between 6PM to 12Midnight (including weekends). Between 8PM to 9PM, the Teaching Assistants will be also available over Live Zoom Meeting for Doubt Clearance.
Discover networking tips, online job search tactics, and ways to stand out from the competition.
Elevate your skills and credibility with our certification.
SQL is the most underrated skill of a Data Engineer. It is used to pull required data points from the complex database of clients. You need to write long queries using joins to get the relevant data points.
Python is the backbone of Data Science. It is the most widely used language for DE. It’s very easy to learn compared to other languages and non-tech people can also learn it. You need not become an expert in it. You should mainly know how to manipulate data using it.
Statistics is what makes Data Science unique. Lots of Data Science problems are solved using statistics tests. Also understanding the dataset is done using statistics. It is very important for interviews.
Tableau is a software that offers collaborative data visualization for organizations working with business information analytics. In this course we have covered tableau from basics to advance which will help any individual to clear data analyst interviews.
Microsoft Power BI is a business intelligence platform that provides nontechnical business users with tools for aggregating, analyzing, visualizing and sharing data. In our course we have covered all aspects of powerbi necessary to clear data analyst interviews with different case studies to showcase in your resume.
Excel is a spreadsheet program from Microsoft and a component of its Office product group for business applications. Microsoft Excel enables users to format, organize and calculate data in a spreadsheet. Its features calculation or computation capabilities, graphing tools, pivot tables, and a macro programming language called Visual Basic for Applications (VBA).
If you are starting going to start your career in Data Domain then you must have understand of this domain completely. In this section you will get the complete overview of the data science domain and its different key components.
Machine learning is core of Data Science. These are mathematical algorithms which try to find patterns and relationships in the input and output of the given dataset. You need to know the inner workings of the algorithms and also how to do hyper parameter tuning.
Deep Learning is a subset of Machine learning. It deals with neural networks which solves complex problems of Computer Vision, Natural Language Processing and time series predictions. Someone will to target advance Data Science roles must have this skill.
Amazon QuickSight allows everyone in the organization to understand data by asking questions in natural language, exploring through interactive dashboards, or automatically looking for patterns and outliers powered by machine learning. It is also an add on tool for resume and shows your desire for learning.
Data Studio is a free tool that turns your data into informative, easy to read, easy to share, and fully customizable dashboards and reports. It is not a necessary tool for you but it's good to add extra tool in your resume to show your fire for learning. It can be helpful if your company decides to use this tool for data analysis.
DSA is not a prime necessity of Data Science but some companies do ask DSA related questions specifically the product based companies like Amazon
R is not widely used as compared to Python but still some companies use it. It’s very power when it comes to plotting variety of graphics. The Exploratory Data Analysis is done better with R as compared to python.
Kaggle is a good place to participate in machine learning/ deep learning competitions. This course covers about kaggle platform and how you can utilise kaggle to build your portfolio. It explains how you can use dataset, notebooks, competition here to get medals and boost your portfolio.
✅ Intro to Big data
✅ Hadoop and its evolution
✅ HDFS Architecture
✅ Hadoop ecosystem intro
✅ Linux commands
✅ HDFS commands
✅ Intro to Map Reduce
✅ Different phases of Map Reduce
✅ Combiners and Partitioners
✅ Hash Function in Map Reduce
✅ Shuffling and sorting in Map Reduce
✅ Map Reduce Use Case
✅ What is Hive
✅ Hive Query Language
✅ Comparison Hive vs RDBMS
✅ Hive Architecture
✅ Hive Views
✅ Hive Subqueries
✅ Built-in Functions
✅ Partitioning
✅ Bucketing
✅ Ranking
✅ Sorting
✅ Hive File Formats
✅ Introduction
✅ Sqoop Import
✅ Sqoop Eval
✅ Sqoop Export
✅ Connecting to MySQL
✅ Sqoop Incremental
✅ Sqoop job creation
✅ Introduction
✅ Properties of HBase
✅ RDBMS vs HBASE
✅ HBASE Architecture
✅ HFile
✅ Zookeeper
✅ Update HBASE Data
✅ Delete HBASE Data
✅ Cassandra Overview
✅ HBASE vs Cassandra
✅ Filters in HBase.
✅ Scala Introduction
✅ Why Scala
✅ Datatypes
✅ Strings
✅ If/else
✅ For Loop
✅ While Loop
✅ Functions
✅ Arrays
✅ Lists
✅ Tuples
✅ SetMap
✅ Functional Program
✅ Anonymous Function
✅ Recursion
✅ Scala Operators
✅ Scala Type System
✅ What is Spark
✅ Spark comparison with Map Reduce
✅ RDD/DAG
✅ Immutability
✅ RDD Lineage
✅ Accumulators
✅ Spark Stages
✅ Spark on Yarn
✅ Spark Storge
✅ Intro to SparkSQL
✅ Handling columns in Dataframe/dataset
✅ Aggregations
✅ Window Aggregations
✅ Joins using Data Frame
✅ Broad Cast Join
✅ Shuffle sort-merge join
✅ Spark optimization
✅ Spark Streaming
✅ Introduction
✅ Kafka Architecture
✅ Index
✅ Cluster
✅ Integrating Kafka with Spark
✅ AWS EMR
✅ OnPrem vs Cloud
✅ HDFS vs S3
✅ What is S3
✅ EC2
✅ Elastic IP
✅ AWS storage, networking
✅ S3 and EBS
✅ Athena
✅ AWS Glue
✅ AWS Redshift
✅ Intro to Apache Airflow
✅ Airflow Architecture
✅ Airflow Installation
✅ Creating and viewing DAG
✅ Cron job creation
✅ Logs Viewing
✅ Sensors
The LinkedIn Growth course teaches users how to build a strong and effective LinkedIn profile, grow their professional network, and use LinkedIn to find new career opportunities. The course covers a range of topics, including profile optimization, content creation, network building, and job search strategies, and is designed to help users improve their visibility and influence on the platform.
This course teaches you how to create a strong and effective resume that highlights your skills and experience, and how to tailor your resume to specific job postings. The course covers a range of topics, including resume formatting, keyword optimization, and cover letter writing, and is designed to help you stand out from other applicants in a competitive job market.
You will be learning about other online job portals hack that will increase your chances to getting call for interviews. It covers Naukri, AngelList, Hirect etc
The HR Round Interview QnA course can help you improve your chances of success. This online learning program covers a range of common interview questions and provides tips on how to answer them effectively. The course also includes information on how to prepare for an interview, how to make a positive first impression, and how to follow up after the interview.
Some companies keep first round as aptitude to check thinking skills. In this course we have covered aptitude topics with their examples which are widely asked in aptitude round of interviews. This course is divided into Quantitative, logical and verbal aptitude sections. It will help learners to build logic on all 3 levels of aptitude.
You will get recorded Interview Mock Sessions that will help you to understand the Interview Process and question types. It covers Python, SQL, Machine Learning, Statistics etc Mock Interview Session and we keep updating it.
Machine Learning & Deep Learning Projects are essential to showcase in your resume to reflect the learnings of your skillset. These projects will have the same level of detailed work as required in an actual company project. That's why we have selected different problem statements from computer vision, NLP and time series which you can work on to excel in Deep Learning.
Data analytics projects are important for businesses and organizations as they enable the collection, analysis, and application of data-driven insights for informed decision-making, process optimization, and improved performance.
A data pipeline is the art of designing and building systems for collecting storing and analyzing data at scale. Organisations have the ability to collect massive amounts of data and they need the right people and technology to collect this huge amount of data so it is in a highly usable state by the time it reaches data scientists and analysts.
In this section, we will be building end-to-end data pipelines using the big data tech stack that we have learnt in the course
I have transitioned my career from Manual Tester to Data Scientist by upskilling myself on my own from various online resources and doing lots of Hands-on practice. For internal switch I sent around 150 mails to different project managers, interviewed in 20 and got selected in 10 projects.When it came to changing company I put papers with NO offers in hand. And in the notice period I struggled to get a job. First 2 months were very difficult but in the last month things started changing miraculously.I attended 40+ interviews in span of 3 months with the help of Naukri and LinkedIn profile Optimizations and got offer by 8 companies.
Based on my career transition and industrial experience, I have designed this course so anyone from any background can learn Data Science and become Job-Ready at affordable price.
