Key Features
Data Science course content at Mindmajix is designed by the expert authors who hold firm real-time experience in artificial intelligence, machine learning, deep learning, and many other latest technologies. Our latest 2020 Data Science course curriculum focuses on present industry requirements and helps you to successfully crack data science interviews and upgrade your career path. You will learn the complete data science syllabus under the following sections
This session introduces you to the fundamental concepts of Data Science.
Topics covered in this section are:
Data science life cycle
Significance of Data Science in this data-driven world
Applications of Data Science
Introduction to big data and Hadoop
Introduction to machine learning, deep learning, R programming, and R Studio
Learning outcome: By the end of this session, you will gain complete knowledge of how Data Science works in real-time and installation of R studio on your machine. You will also become familiar with simple calculations and logic using R loops, operators, and switches.
Data Exploration section is one of the essential topics of Data Science training. Data exploration is an approach that is similar to initial data analysis where a data analyst uses it to understand what a data set is and know the characters that a dataset contains.
Topics that we cover in this section are:
Importance of data exploration in Data Science
Extraction and exporting of data from various external sources
How to conduct data exploration using R?
Data exploration methods
Working with data frames
Operator in-built functions
Looping statements and user-defined functions
Matrix, list, user-defined functions, and arrays.
Learning Outcome: By the end of this session, you will gain hands-on expertise in accessing elements of churn data, usage of R to modify and extract the results from the data set.
Data manipulation is one of the important concepts of Data Science. It helps in organizing data into an easily understandable format.
Topics covered in this section are:
Introduction to data manipulation
Need for data manipulation
Discussing various functions such as mutate() function, sample_frac() & count() functions, Sampling & Counting with sample_n()
Learning Outcome: By the end of this session, you will gain hands-on expertise on how to implement DPLR to perform various operations such as data abstraction, data manip, and storing.
Data visualization is the internal and crucial part of Data Science. This section helps you to understand how to extract the hidden trends out of data and represent them in the form of charts and graphs.
Topics covered in this section are:
Introduction to visualization
Explanation of different charts and graphs
Introduction to graphics
Building frequency polygons with geom_freqpoly
Numerical distribution with geom_hist() function,
Visualization with Plotly package & building web applications with shinyR,
Univariate Analysis with Bar-plot, histogram and Density Plot, and multivariate distribution,
Bar-plots for categorical variables
Visualization with Plotly package & building web applications with shinyR,
Continuous vs categorical with box-plots,
Intro to plotly & various plots, visualization with ggvis package, and themes to make the graphs more presentable,
Visualization with ggvis package
Building web applications with shinyR.
Visualization with ggvis package,
Learning Outcome: Upon completion of this module, you will come to know how the data visualization works and the customer churn ratio with the help of using ggplot2, Plotly for importing and analyzing data into grids. You will also come to know how to scatter plot works in real-time.
Statistics is an integral part of data science and plays an important role in it. Multiple statistical methods available are regression, classification, time series and hypothesis testing; data scientists use all these methods to run suitable experiments and also to summarize the data fairly & quickly.
Topics covered in this segment are:
Introduction to statistics and relation between Data Science and statistics.
The terminology used in statistics & categories of statistics.
Central Tendency, Correlation & Covariance, Measures of Spread, standardization & normalization
Probability & its types
Chi-Square testing, hypothesis testing, a binary distribution, normal distribution, and ANOVA
Learning Outcome: You will gain complete knowledge on building a statistical analysis model that uses representations, quantifications, experiment data for collecting, reviewing, analysis and drawing conclusions from data.
Projects
Project Description: This project deals with doing predictive analysis based upon the available data as to which insurance policy will be beneficial for a particular age group of people.
Domain: Insurance
This project covers the following topics
Statistical analysis
Probability and its types
Association rule
Recommendation engine
Collaborative user-based filtering
Project Description: This project will help you in analyzing the available traffic on the road in a particular area at a specific time period. This works on capturing the GPS location of mobile phones. It calculates the number of mobiles available in that area at that time and predicts the traffic situation accordingly.
Domain: Social
This project covers the following topics:
Data visualization
Data mining
Plotting charts, graphs, bars, etc
Correlation and covariance
Project Description: In this project, you will work on types of customers and their shopping behaviours. Every individual has a different type of mood, choice, and shopping pattern and you can categorize your customer more or less under a particular category. Based upon their category, you can predict their choices and decision whether he/she is going to buy or not.
Domain: Retail
This project covers the following topics:
Project Description: This project deals with understanding the real-time problem statement, manipulating data, and then building an application.
Domain: Mobility
This project covers the following topics:
Correlation and covariance
Probability
K-means
Cost complexity pruning, pre-pruning, and post-pruning
Project Description: This project helps you to manipulate the available data at that location to predict whether setting up a new venture will be profitable or not.
Domain: Social
This project covers the following topics:
Introduction to component analysis, PCA in R, and procedure to implement PCA
K-means
Data mining, visualization, clustering
Decision trees and random forest
Confusion matrix, accuracy, true positive rate, false-positive rate
Project Description: You will do a thorough analysis of the previous trends of the company before buying its share.
Domain: Investment
This project covers the following topics:
Regression analysis
Random forest in R, and other data implementation techniques
Cross-validation and building logistic models based on real-life applications of regression
Probability
Project Description: This project is quite interesting when you are willing to change your job stream. This is a bit risky when you are entering into a new field altogether. You have to analyze the pros and cons, such as cost of undergoing training, efforts, time, waiting period probably and most importantly salary for the new role. You can use TensorFlow in R, and deep learning on the ground data to make the decision.
Domain: Human resource
This project covers the following topics:
TensorFlow in R
Deep learning
Probability
Data mining and visualization
Project Description: In this project, based upon user’s genre preferences, using R programming you can model a recommendation system that can suggest a movie to watch.
Domain: Entertainment
This project covers the following topics:
Artificial intelligence and deep learning
Evaluation with ROCR, detailed formulas
Evaluate performance metrics
Predictive analysis using linear regression
Project Description: This project will help you prepare a system using machine learning algorithms and R programming to detect the credit card fraudulence.
Domain: Finance
This project covers the following topics:
Machine learning algorithm
R programming
Canopy clustering, Hierarchical clustering, and Theoretical aspect of K-means
Probability
Project Description: Uber takes help from data analysis greatly to expand its reach rapidly. This project helps you to learn how Uber takes a decision, improves marketing strategy, offers promotional deals using data analytics.
Domain: Transport
This project covers the following topics:
17 Jan, 2021 - 16 Feb, 2021
20 Jan, 2021 - 04 Feb, 2021
23 Jan, 2021 - 27 Feb, 2021
24 Jan, 2021 - 23 Feb, 2021
27 Jan, 2021 - 11 Feb, 2021
30 Jan, 2021 - 06 Mar, 2021
Besides providing fundamentals of Data Science, Mindmajix training assists you in completing the valuable certifications, taking up real-time projects, and helps you in placements in the top companies of the industry. There are various options available based upon your availability to take up this training -- Self-paced training, Online instructor-led training, and corporate training.
Furthermore, Mindmajix offers you Data Science training with the Python language, which is a user-friendly English-like language and easy to learn. Python is most commonly used these days because of its simple syntax, robust library, portability, and web usability.
Mindmajix also encourages you for this training by providing you 24/7 support, allows you to pay in two instalments, and most importantly, it can be designed based upon your specific needs.
The demand for Data Scientists is increasing every day. Huge data is available in the market, but the challenge lies in analyzing this database that shows the road map for business to grow. These days, companies are in tough competition to leverage big data analytics and data science to get the nerves of users first, to benefit from the first mover’s advantage.
According to a survey conducted by IBM, up to 2,720,000 data scientists job openings will be there in 2020.
Every organization has realized that they need data scientists to gain maximum benefit from the available data.
Almost all the sectors including cyber-security, healthcare, defence, education, IT need data scientists.
Getting certified in Data Science is beneficial for the following job roles:
Your interest and willingness is the only thing you need to have for attending this training. Even if you can’t pay the whole amount at one time, we encourage you to pay in two instalments but don’t stop you from the enrollment. Mindmajix is completely focused on your learning, gaining knowledge, and getting a good job.
After completing this training, the learners will be in a position to master the following areas:
Based upon the responses received by Payscale.com, the average salary of an entry-level data scientist can be 508,682/-. IT professionals with 5-9 years of experience can expect an average salary of 610,811/- whereas, with 10-19 years of experience, a Data scientist can expect 1,724,618/-
In the US, a Data Scientist can earn $ 113,309 on an average.
This is a prestigious job, the name Data Scientist itself has a great weightage in itself. When compared to other jobs on the same level of experience and for the similar kind of educational background, you earn more comparatively. It’s just a matter of your interest! If you are interested in working smartly and creatively, and earn more, this role is waiting for you.
The first milestone for a Data Scientist aspirant is to learn programming languages such as Python, R and get hands-on analytical tools such as SAS. The next stage could be getting knowledge of big data analytics and statistical tools, for example, Hadoop, Spark. Yet another milestone could be understanding of visualization, charts, maps, and reports to analyze the large chunk of data.
You as a Data Scientist have enough potential to give the direction to your business -- the shortest path to succeed. You perform data analysis, data mining, statistical analysis using available tools to predict the solutions for better business performance.
Almost all companies have started creating positions for Data Scientists including Microsoft, Google, Amazon, Accenture, IBM, and Capgemini.
Our Data Science course covers all the topics that are required to clear Data Science certification. Trainer will share Data Science certification guide, Data Science certification sample questions, Data Science certification practice questions.
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Yes, you get two kinds of discounts. They are group discount and referral discount. Group discount is offered when you join as a group, and referral discount is offered when you are referred from someone who has already enrolled in our training.
The trainer will give Server Access to the course seekers, and we make sure you acquire practical hands-on training by providing you with every utility that is needed for your understanding of the course.
The trainer is a certified consultant and has significant amount of experience in working with the technology.
Yes, we accept payments in two installments.
If you are enrolled in classes and/or have paid fees, but want to cancel the registration for certain reason, it can be attained within first 2 sessions of the training. Please make a note that refunds will be processed within 30 days of prior request.
User Reviews on popular courses
Earlier I have taken many online training courses but definitely Mindmajix is the best among them. The quality they maintain is appreciable. Training sessions are well structured and the trainer explained each and every concept with real-time scenarios. I truly recommend this course for the learners who want to gain expertise in Data Science.
Checking other reviews, first time I have enrolled for the Data Science course from Mindmajix and it was really excellent. The trainer was an experienced professional and covered concepts with real-time examples. This made me easy to understand and I thoroughly enjoyed training sessions.
I have learned a lot from this training which I missed in my previous training institute. You helped me understand the data science concepts really well. Thankyou Mindmajix for your efforts.
I took .NET training from Mindmajix. I must say the course content was highly qualitative and the trainer covered all concepts. Overall it was a good experience with Mindmajix.
Thank You for the sessions that helped me gaining knowledge in Spotfire training. Trainer's experience helped me to get the detailed information regarding the key concepts and challenging tasks in real-time. Thanks once again.
Perfect sessions to know all the key concepts of Spotfire certification training. Thanks to the support team as well. Thanks to Mindmajix.
Servicenow training offered by MindMajix is excellent, and you clear Servicenow certification very easily after attending this training, and also you will get the real time view of the Servicenow.
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