Data Science Training

Data Science Training

Jovi soft solutions offer you the best Data Science training. We have designed this course with the help of industry professionals to cover all the lifecycle concepts of data science which includes Business analytics, master data analytics, Machine learning algorithms, Data extraction, data cleansing, data transformation, feature engineering, building prediction models, data mining, data integration, etc. In this data science course, you will also be exposed to a recommendation engine that allows you to build a product recommendation algorithm for the retail and entertainment industry. To prepare you for the sexiest job of the 21st century we follow the updated data science syllabus.
Enroll now into Jovi soft online Data science program to learn from the real-time data scientists.

Overview of Data Science Training

Well, as a Data Scientist it is very important to understand the business problem first. In your meeting with clients ask relevant questions, understand and define objectives for the problem that needs to be tackled. You should be curious to ask a lot of questions which is one of the many traits of a good Data Scientist.
Now gear up for Data Acquisition to gather and scrape data from multiple sources like SAP servers, logs, databases, API’s and online repositories. It seems like finding the right data takes both time and effort.

After the data is gathered comes data preparation, this step involves data cleaning and data transformation. Cleaning is the most time-consuming process as it involves handling many complex scenarios like dealing with inconsistent data types, misspelled attributes, missing vales, duplicates values and whatnot.
Then in Data transformation, modify the data based on defined mapping rules. In a project ETL tools like Talend and Informatica are used to perform complex transformations that helps the team to understand the data structure better than understanding what you actually can do with your data is very crucial. For that Data Scientist should do exploratory data analysis.

With the help of EDA , define and refine the selection of feature variables that will be used in the model development. Now proceed to the core activity of a Data Science project such as Data Modelling. She repetitively applies type force machine learning techniques like KNN, decision Tree, Naive Bayes to the data to identify the moral that best fits the business requirement.
Train the models on the training data set and tests them to select the best performing model. Prefer Python for modelling the data. However it can also be done using R and SAS.

Well, the trickiest part is not over Visualization and Communication, meet the client again to communicate the business findings in a simple and effective manner to convince the stakeholders. She uses tools like Tableau, Power BI and QlikView that can help her in creating powerful reports and dashboards and then finally deploy and maintain the model. She tests the selected model in a pre-production environment before deploying it in the production environment which is the best practice right?
After successfully deploying, use reports and dashboards to get real-time analytics further monitor and maintain the projects performance. Well, that’s how we complete the Data Science project. We have seen daily routine of a data scientist is a whole lot of fun, has a lot of interesting aspects and comes with its own share of challenges.

How Data Science is changing the world?

Data Science techniques along with genomic data provides a deeper understanding of genetic issues in reaction to particular drugs and diseases. Logistics companies like DHL, Fedex have discovered the best routes to ship the best suited time to deliver. The best mode of transport to choose thus leading to cost efficiency. With Data Science it is possible to not only predict employee attrition but to also understand key variables that influence employee turnover. Also the airline companies can now easily predict flight delay and notify the passengers beforehand to enhance their travel experience. Well, if you are wondering there are various rules offered to a data scientist like Data analyst, Machine learning Engineer, Deep Learning Engineer, Data Engineer and Data scientist can range from $95,000 to $165,000 dollars. Are you ready to be Data Scientist? IF yes, then start today the world of data needs you!

Data Science Online Training Objectives

1. About Data Science Training.

With this Data Science Course, the learners will be in a position to master the following areas:
Machine Learning algorithms
Roles and responsibilities of a Data Scientist
Linear and logistic regression
Integrating R with the Hadoop ecosystem

2. Who can learn Data Science ?

Aspiring professionals of any educational background with an analytical frame of mind are most suited to pursue the Data Science course, including:
Analytics Managers
IT Professionals
Business Analysts
Marketing Managers
Banking and Finance Professionals
Beginners or Recent Graduates in Master’s or Bachelors Degree
Supply Chain Network Managers

3. Prerequisites for Data Science Training.

Professionals wishing to succeed in this Data Science training course should have:
Basic knowledge of any programming language
Basic knowledge of statistics

4. What are the roles and responsibilities of a Data Scientist ?

You as a Data Scientist can possibly provide guidance to your business - the briefest way to succeed. You perform data mining, data analysis, factual analysis utilizing accessible tools to predict the solutions for better business execution.

5. Which are top hiring companies for Data Scientists ?

Almost all companies have started creating positions for Data Scientists including IBM, Google, Microsoft, Accenture, Amazon, and Capgemini.