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Prodigious, Challenging and Real Time Data Science Projects for Aspiring Data Scientists

Getting a job in data science can seem intimidating. No Matter you are a beginner, professional, wants to change your technology or upskills. We help learners for developing a keen sense of how to solve different business problems that will set you apart from the crowd. For the real progress along the path toward to becoming a data scientist, it’s important to start building data science projects. Many new bees of data science spending a lot of time to learn theory and not even concentrate on practical application.


What is Data Science?

Data Science – The New Cash Cow

  • Data Science is a term that escapes any single complete definition, which makes it difficult to use, especially if the goal is to use it correctly. However, 
  • Data science – its methods, goals, and applications – evolve with time, and technology. Data science 25 years ago referred to gathering and cleaning datasets and then applying statistical methods to that data. 
  • In 2018, Data science has grown to a field that encompasses data analysis, predictive analytics, data mining, business intelligence, machine learning, deep learning and so on.

LET’S BREAK THINGS DOWN

The Data in Data Science

  • What do you do to data (big and traditional)?
  • Where does data come from?
  • Who handles the data?

Data Science Explaining the Past

  • What does Business Intelligence do?
  • Where is Business Intelligence used?
  • Who does the BI branch of data science?

Project significance in Training
Projects are some of the best investments of your time. You’ll enjoy learning, stay motivated, and make faster progress. Projects help you improve your applied data science skills quickly while giving you the chance to explore an interesting topic. You can add projects into your portfolio, making it easier to land a job, find cool career opportunities, and even negotiate a higher salary. Learn the most in-demand technologies in data science such as Python, Pycharm, ChartJS, Data Analysis, Segmentation, Algorithms and implement concepts like Data Exploration, Regression Models, Hypothesis Testing, etc.

Project approach and methodology
The best way to showcase your skills to become a strong portfolio of data science projects. If you are trying to build some data science projects by yourself to improve your resume in between you felt you are struggling by the size of the code and a lot of concepts involved in it. We know how to teach you the complete implementation of a project right from the scratch. We are focusing on practical approach, Project-Based Learning that can develop learner skill through practical work and application. If you are looking for data science project-based learning and an expert who can teach. You are on the right track, we have various prodigious data science projects that will boost your portfolio, and help you to get your dream job in the field of Data Science. There are many methodologies and conceptual knowledge we are sharing with our candidates in the beginning of the project like

  • What is Data Science?
  • Introduction to Data Science
  • Why to learn Python? 
  • Why python is necessary for Data Science? 
  • How data is very important for companies? 
  • How to play with data?

We’ll share data science project with our aspiring data scientists that will help them to understand what a completed project should look like.

Companies looking for Data Scientists
In a growing manner companies facing critical shortage of data scientists who can synthesize huge amounts of information from multiple sources, derive new insights, convert data into actionable information, and articulate their findings. As you know data is everywhere and the data is very important for everyone. Companies are receiving data from various sources like ERP, cloud, websites, customers data, social data and more... according to 2019 last glassdoor data, data scientists are in high demand. With a median base salary of $108,000 and plenty of opportunity. We have done many researches and found keen projects after analysis. We have completed those projects which is built by our experts after investing efforts and time. We bring those projects for our aspiring data scientists associated with our Advanced Data science certification training and project bootcamp. This Project Based Training Program brings together the technology and analysis with the help of our experts for our candidates and learners. 

What does a Data Scientist do?

what_does_data_scientists_do


In simple terms, a data scientist’s job is to analyze data for actionable insights

  • Identifying the data-analytics problems that offer the greatest opportunities to the organization
  • Determining the correct data sets and variables
  • Collecting large sets of structured and unstructured data from disparate sources
  • Cleaning and validating the data to ensure accuracy, completeness, and uniformity
  • Devising and applying models and algorithms to mine the stores of big data
  • Analyzing the data to identify patterns and trends
  • Interpreting the data to discover solutions and opportunities
  • Communicating and findings to stakeholders using visualization and more...

Data Science Projects for Aspiring Data Scientists
Project building is very important and working on project is a very keen thing. As you are an aspiring Data Scientist and haven't worked on project yet and you are thinking to start building your own it's a great time to start. When it came time to start our own project we tried to apply the same processes and steps to build a data science project. It was quickly obvious that this would be a long learning process we needed to adjust our way of thinking in a quick manner and take the decisions in a better way. This is not a silver bullet formula since the field and technology is changing rapidly and we react to changes on a daily basis ourselves. Getting a data scientist job after completing data science training or becoming successful as a data scientist will depend on your ability to sell yourself. Working on interesting data science problems is a great way to kick-start your career as an enterprise data scientist. Highlighting various data science project examples on your CV will carry more weight than telling them how much you know.

Data_science_projects_for _aspiring_data_scientists


Learn data science with python in our data science bootcamp project program you will find how to build projects for scratch by your own. We have a team of visionary technology experts and analyst sharing their experience with our learners and candidates in our data science bootcamp project training program. This project based training program will definitely can change the way of life, way of vision, and interaction with the world of data science algorithms, concepts and mindset. You will learn how to handle open-ended real-life challenges and problems that professional data scientists do. Our experts help you to unlock the doors, building your confidence and making you ready for an exciting new data science career.

Why Python is the Best language for Data Scientists?
We often get emails from learners asking whether should use Python or R when performing day-to-day analysis tasks. Both Python and R are among the most popular languages for data analysis, and each has its supporters and opponents. Anyone interested in how these two programming languages compare to each other from a data science and analytics perspective, including their unique strengths and weaknesses. 

Python is the preferred programming language for data scientists. They need an easy-to-use language that has decent library availability and great community participation. Professionals working with data science applications don’t want to be bogged down with complicated programming requirements. They want to use programming languages like Python to perform tasks hassle-free.

  • Python is Easy to Use
  • Python has multiple Libraries and Frameworks
  • Python has Community and Corporate Support
  • Python is Portable and Extensible

A small comparison between R and Python

Parameter

          R

         Python

Objective

Data Analysis

Deployment and Production

Primary Users

Scholar and R&D

Programmers and developers

Flexibility

Easy to use available library

Easy to construct new models from scratch

Learning curve

Difficult at the beginning

Linear and smooth

Popularity of Programming Language, Percentage change

4.25 in 2018

21.98 in 2018

Average Salary

99.00

120.00 

IDE

Rstudio    Spyder

Ipthon Notebook

Integration

Run locally

Well-integrated with app

Task

Easy to get primary results

Good to deploy algorithm

Important Packages and library

tydiverse, ggplot2, caret, zoo

pandas, scipy, scikit-learn, TensorFlow, caret

Database size

Handle huge size

Handle huge size

Disadvantages

Slow High Learning curve Dependencies between library

Not as many libraries as R

Advantage

Graphs are made to talk. R makes it beautiful

Jupyter notebook: Notebooks help to share data with colleagues

You will learn all the ins and outs of data science which includes basics of data science, analytics, statistics, machine learning, data engineering, and deep learning. Many data science beginners are not sure where to start, what data science projects to do, what data science tools and techniques to use. We have made projects, list of hurdles, challenges during development of projects along with their solutions. The right mind set, willingness to learn and a lot of dedication is required to understand the project. If your interest in Data and you are interested in data analytics, or data science we have Prodigious and challenging data science projects for you. There are few data science projects list down are as below:

  • Visualization project
  • Exploratory data analysis project
  • Forecasting project
  • Time series Analysis project
  • Lead Analytics project
  • CRM project

So that when candidate performing data analysis on different kinds of data using a wide variety of skills you can say you will be either mastered or are in the process of mastering, solving a real-world problem using the required skills. To explain we’ll take an example of one of our Project called "Lead Analytics". We have built the project and sharing with our Data Science aspirants for good hands-on. Suddenly comes a question in your mind "what is Lead Analytics" and "what it does?". In this Lead Analytics Project, you can actually implement data science methodology, skills and fundamentals and concepts. If you are thinking to put yourself to work on Real Data Science Project but you don’t know where to start, it's a good idea take advice from our experts acquired throughout the course. 

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