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Apponix Technologies

Data Science with Python Certification Training Course With Placement Assurance

Overview of Data Science Training Course

This course follows a curriculum that covers all the major aspects of data science such as machine learning,data integration, data architecture, data visualization, predictive analytics, etc.


Benefits of learning Data Science

Data science-related courses from Apponix will let you make the most out of the demand for skilled professionals in this sector so that you can land a high-paying job at your dream company.

With our data science certificate online or offline course, you will surely be able to have a competitive edge over other applicants interested to have a lucrative career in the field of data science.


Data Science related jobs

  • Data Analyst
  • Data Scientist
  • Data Engineer
  • Data Architect
  • Analytics Manager/Lead
  • Machine Learning Engineer
  • Statistical Programming Specialist

2000+ Ratings

3000+ Learners

Testimonial

Skills Covered in Data Science

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Python full coding from scratch
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Visualization with Python
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Machine Learning with Python - 6 different algorithms
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Robotic Automation
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Multiple Linear regression
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Logistic regression
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Cluster Analysis
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SQL queries(with Python)
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Data Science Courses

What is the scope of data science career?

Because it is rated as one of the top job sectors in terms of career growth opportunities, job satisfaction and pay scale. Furthermore, the demand for data scientists is always high as the number of skilled professionals is comparatively less.

Can I learn data science even if I don’t have any prior knowledge about this field?

Yes, you can learn data science even if you do not have any prior knowledge about this field as we will also take classes on basic concepts of data science.

Our complete data science Bootcamp does not come with exams and certification but an industry-recognized data science course completion certificate will be offered after you score 80 % at the one-hour-long exam we will conduct that will contain 25 objective-type questions about the course.

Data science is an umbrella term for the processes a data scientist uses to uncover patterns all the while extracting business-critical information from huge amounts of data derived from various sources.

Why Should You Learn Data Science ?

  •  28-35% of boost in the field since 2023
  •  Expecting massive recruitment
  •  Handsome salary ranges from around 3.5 to 10 lakhs per year
  •  Majority of the firms are moving to be insights-drive which increases the trends in and around big data, AI, cloud computing, etc. This enhancement of data maturity heightened the need of data science
  •  Huge investment of MNCs in Big Data and AI sectors which demands greater implementations of Data Science
  •  Along with analyzing and comprehending the data trends, a data scientist has to interpret and decipher the laws in an appropriate and approachable manner for the business tycoons, and also formulate advance solutions over it.
Career

Data Science Training Key Features

60 Hrs Practical Sessions
Guaranteed 5 Interviews
Assured Job Placement
CV Building activities
Interview preparation
Mock Interview sessions
100% Money-Back Guarantee
Delivered by Senior Data Scientist
18 Case studies on Machine Learning
IABAC Certified Data Scientist Certification
Linkedin Learning Premium access for 12 months
IABAC Certification Voucher for Free worth $136
Certificate from JainX Academy - Unit of Jain University

Data Science Course Objectives

  •  Python full coding from scratch
  •  Visualization with Python
  •  Statistics - theory and application in business
  •  Machine Learning with Python - 6 different algorithms
  •  Multiple Linear regression
  •  Logistic regression
  •  Variable Reduction Technique - Information Value
  •  Forecasting - ARIMA
  •  Cluster Analysis
  •  Decision Tree
  •  Random Forest
  •  Case studies on Machine Learning (18 case studies)
  •  SQL queries(with Python)
  •  Business Presentation of Technical Solution in-front of end client.
  •  Robotic Automation(with Python)
  •  CV Building activities
  •  Interview preparation
  •  Mock Interview sessions

Fees & Training Options

Online Training

$

  • Interactive Live Training Sessions
  • 60+ Hrs Practical Learning
  • Delivered by Working Professionals
  • 1 Year Access to Recorded Sessions
  • Placement Assurance
  • Guaranteed 10 Interview Arrangements
  • Weekdays & Weekend batches
  • Authorized IABAC Training Delivery
     
Enroll Now

Data Science Training Syllabus

Prerequisites

No prerequisites for learning data science but if you have some previous knowldge on computer science & statistics it helps you a lot in understanding subjects fast.

Secondly, you need to have an analytical mind – that is all you would need to enroll for Statistics For Data Science Courses.
 

Data Science Course Syllabus

Machine Learning with Python
1:Introduction to Python Programming Language
  •  Introduction and Installation of Python software Python packages: Pandas, & Numpy
  •  Concepts of Data frame Filtering
  •  Loc and iloc for filtering Usage of Boolean in Filtering Appending
2: Data handling in Python
  • Handling of Missing values If else statement
  •  Extra trick of using if else statement Removal of Duplicates
  •  Frequency Distribution
  •  Merging – Inner, Outer, Left and Right Binding and Appending
  •  Descriptive Statistics
  •  Inbuilt Numeric functions of R
3: More data handling using Python
  • Pivot Table of Excel in Python Grouping function
  •  Learning of SQL queries using Python Grouping numeric data
4: Additional functions of Python
  • Text functions
  •  Data cleaning with efficient text functions Inbuilt String functions of Python Reshape functions of Python
5: Statistic
  • Everything you want to know about statistics….Well sort of!! Mean, Median, Mode
  •  Standard Deviation, Variance, Normal Distribution Hypothesis testing
  •  T-test, Anova, Normality test
6: Linear Regression
  • Predictive Analytics – Linear Regression Concepts of Linear Regression
  •  Simple and Multiple Linear Regression Automatic Dummy Variables creation technique Model Validation parameters
  •  Model Assumption testing
  •  Splitting of data for Validation and testing
  •  Business Case Study with real data to model in Python
7: Linear Regression Practice Case Study

Participants will be asked to develop a Linear Regression model on a real life data, in presence of the instructor. Time given is 2.5 hours. Participants will be treated like an industry employee, but in terms of help certainly the instructor will not be as ruthless as the boss. After completion of the model (with the help of the instructor wherever it is required), the instructor will show how to present a model to a real life client.

8: Logistic Regression
  • Predictive Analytics – Logistic Regression Concepts of Logistic Regression
  •  Difference between Linear Regression and Logistic Regression Automatic Dummy Variables creation technique
  •  Model Validation parameters Model Assumption testing
  •  Splitting of data for Validation and testing
  •  Business Case Study with real data to model in Python
9: Logistic Regression Practice Case Study

Participants will be asked to develop a Logistic Regression model on a real life data, in presence of the instructor. Time given is 2.5 hours. Participants will be treated like an industry employee, but in terms of help certainly the instructor will not be as ruthless as the boss. After completion of the model (with the help of the instructor wherever it is required), the instructor will show how to present a model to a real life client.

10:Time Series Forecasting
  • Time series forecasting: ARIMA
  •  Difference between forecasting and prediction Concepts of time series data
  •  Concepts of ARIMA
  •  Descriptive analytics for ARIMA Development of model
  •  Best model selection Forecasting with the best model Residual analysis
  •  Business Case Study with real data to model in R software
  •  Participants will be asked to develop a model in presence of the instructor.
11: Cluster Analysis
  •  Unsupervised Machine Learning with R Cluster Analysis: Concepts
  •  Cluster analysis with R – K Means, Hierarchical etc.
12: Decision Tree and Random Forest

oncepts of Decision Tree Decision Tree with Python Concepts of Random Forest Random Forest with Python

R Programming
1: Introduction to R Programming Language
  •  Introduction and Installation of R software R packages
  •  Concepts of Vector – Numeric, Character, and Factor Concepts of Data frame
  •  Filtering
  •  Usage of Boolean in Filtering Sorting
  • Reshape of data using Tidyr package
2: Data handling in R
  • Handling of Missing values If else statement
  •  Extra trick of using if else statement Removal of Duplicates
  •  Merging – Inner, Outer, Left and Right Binding and Appending
  •  Text functions
  •  Data cleaning with efficient text functions Inbuilt Numeric functions of R
  •  Inbuilt String functions of R Inbuilt other functions of
3: More data handling using R
  • Pivot Table of Excel in R Table function
  •  Count function of plyr package Learning of SQL queries using R Grouping numeric data
  •  User defined functions (Macros) in R Visualizing of Data
4: Additional functions of R
  • Date functions with Lubridate package Apply functions
  •  User defined functions (Macros) in R Visualizing of Data
Data Analytics with MS-excel
1: Introduction to Excel
  • Introduction to Excel Workbook and worksheets Entering data into the spread sheet Undo & Redo Adding Comments
  • Formatting and conditional formatting All types of borders Moving & Coping and inserting data Finding and replacing Filtering and Sorting of data
  • Logical operators Practice sessions
2: Different Functionalities of MS Excel
  • Text to column V-look up Duplicate removal Concatenate
  • Functions of excel – Logical, Mathematical, Statistical, Others Practice sessions
3: Analytics with Excel
  • Pivot Table
  • Data manipulation with pivot tables Pivot table charts Data visualization with Excel
  • Practice sessions
4: Advanced Analytics with Excel
  • Pivot Table
  •  Functions of excel – Financial functions What if analysis – Goal Seek, Solver etc. Macros
  •  Analytics using Excel Practice sessions
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Become an IABAC certified Data Scientist

We are certified partner of IABAC.

The International Association of Business Analytics Certification (IABAC™) is a Globally recognized Professional Association dedicated to growing and enhancing the field of applied Data Science and Business Analytics. 

We provide you below exam voucher worth of $220 for free.

Certified Data Scientist Certification (CDS – DS2050)

After the completion of the course we provide you below exam voucher worth of $220 for free.

Certified Data Scientist Certification (CDS – DS2050)

If you clear the exam you will become a Certified Data Scientist.

The Certified Data Science developer certification provided by IABAC, has recognition on a global platform.

It consists of concepts on programming languages like R and Python, the basics of Data Science and Machine Learning, industry cases for data science.

Yes, machine learning is a part of data science.

Exploring, sorting and analyzing big data obtained from various sources in a bid to optimize the internal and external processes of a business is the primary objective of data science.

It is a method of analyzing data. It is also a part of artificial intelligence as it allows computer systems to identify patterns and make decisions without any help from humans.

Certification

Our Top Instructors

Advisor

Mr Shubhojit

Data Science Trainer

WORK EXPERIENCE:-

He has 14 years of experience in the field of Analytics and has worked for different CMMI Level 5 companies like The Nielsen Company (Advanced Analytic Consulting- Price and Promotion team), and TCS. Presently employed with the largest IT company in India - TCS.

Shubhojit has experience in working in multiple domains like Retail, BFSI, Energy, Utility, etc. 

An expert in multiple statistical software like SAS, R, Python, Spotfire, GMP, etc. He is a seasoned professional with extensive experience in Predictive Analytics, Machine Learning, and Simulation. 

Extremely proficient in handling Deep learning algorithms like Artificial Neural Network (ANN), recurrent neural network (RNN), and convolutional neural network (CNN). 

Performed both Regression and Classification models using Deep learning technologies. 

This algorithm was executed with both Python and R. He has also worked with other algorithms like XGBoost, Naïve Bayes, Support Vector Machine, or recommendation engines like Collaborative Filtering, and Market basket analysis. 

Worked with unstructured data using Natural Language processing to deploy sentiment analysis and topic modeling. 

Extensive work experience in visualization tools like Power BI, and Spotfire. The tools were used to connect with different data sources and integrate them to create visualizations for the client to understand their business position. 

He had also used to call Rest API to connect to databases where security concerns were of the highest importance and direct data integration was denied. 

He has also worked for web analytics using Google Analytics to track visitors’ behavior and predict their patterns. This was also integrated with HotJar to create a heat map of customer clicks. 

He has undertaken specific modeling projects for clients including translating client requirements into project specifications, model execution, resolving data, technical and analytical issues, interpreting output, and preparing client presentations and simulators, using Python, R, SAS 9.2, MS Excel, and other software. 

Provided required explanation internally to ensure effective use of output, liaising with AAC Consultants as appropriate. Translated model results into client deliverables and present back to the internal team. Communicated with internal team and client for obtaining information.

Handled projects for companies like Energizer, Nestle, etc. Executed projects for Banking Financial Companies to develop and validate different propensity models extensively. 

Used Logit Model and Churn Model extensively to execute these models. Also used Cluster Analysis extensively. Maintained relationships with other functions/teams and coordinate with modeling consultants, consultants, and practice areas. Extensively used Multiple Regression Analysis and Logistic Regression analysis to run and model the data. 

Used Logistic Regression analysis for the BFSI domain to help the client to focus on their target customer group and formulate their promotion strategy. 

Also worked on Text analytics through R for one of the clients to help them understand their key customer concern areas. Expert in Base SAS, SAS/STAT SAS/Macro, MS Excel and extensively used SQL query, and Global Modeling Platform (GMP). 

He has also been a corporate trainer in the field of analytics for the last 4 years. He has trained different companies like Genpact, HSBC, ITC, Wipro, etc. He has also trained more than 250 students (apart from the corporate training program) to coach them to learn and master Business Analytics. 

He had also been invited to IIT Kharagpur several times, to conduct analytics workshops for their B-Tech students. He has founded Analytics Educator – a premium institute for pertaining analytics training to professionals. 

He is also associated with other institutes like Apponix, IVY Pro Scool, Edu Pristine, etc to impart analytics training.

Career after Data Science Course

Data science is trending as a highly sought-after career among tech enthusiasts and people who want to put in their effort to make the tech industry all the more advanced but with that stated, securing a job as a data scientist is easier said than done.

Why Data Science?

We are IABAC certified.

Well, without proper data science training from an industry-recognized technical training academy like Apponix, one can find that they are struggling to keep up with the competition that will be trained in data science courses online.

IT companies these days have finally understood that they need professionals who are experts in deriving valuable business-critical information from the data they collect from a plethora of sources.

If an IT company wants to invest in data-driven technologies such as automation, machine learning, and artificial intelligence then it will need professionals who are highly skilled and have all the prerequisites of a qualified data scientist.

Since, all services that are currently available to people around the world whether it be their streaming service provider to their preferred Search Engine, use the data-driven technologies mentioned above, it is evident that the demand for data scientists will witness an exponential increase in the coming years!

With that stated, if you are on the hunt for quality-assured data science training online then choose Apponix – as we have been offering our data science course with placement since 2014.

Over the years, our data science training course has helped countless students find their way amidst the cutthroat competition and secure a high-paying job as a data scientist in leading tech companies in India and abroad.

For more details, feel free to get in touch with us.

 

Career

Data Science Course Reviews

Client

Resham Rajpal

Data Science Expert

The training at Apponix made me more confident in Data analysis. I have completed Data Science training form here. Excellent classes that helped a lot.

Client

Ajith Bahadhur

Data Science Analyst

My experience with Apponix was really great. The trainer provided a lot of practical training. He is an expert. Each topic was taught through proper practical classes.

Client

Mahesh Mahi

Data Science Analyst

I took Data Science training from the institute. I am happy to make Apponix as my choice. Too good labs and sessions are handled here.

Client

Lakshana Senthil

Data Engineer

Management is very good, flexible with timings. Teaching pattern is easy and understandable.

Client

Bijal Patel

Data Analyst

Best institute for Data Science. Trainer has very good knowledge in Data Science.

Client

Aarsh Mehta

Data Engineer

Sir is very helpful and takes every step to make the students understand topics.

Frequently Asked Questions

Yes, you need to have basic knowledge about various programming languages like Python, C/C++, SQL, and Java alongside a basic understanding of computer coding.

 All courses available online  & Offline classes are available in Bangalore, Pune, Chennai only.

It is mentioned under the training options. Online, Offline & self paced learning course fees differs.

Course duration is 2 months or 60 Hrs Usually daily 2 hrs.
 

Yes, We provide course completion certificate on web design & development. apart from this there is 1 more certificate called as “ Apponix Certified Professional in Data Science”
If you score more than 80% in the exam you will be awarded as “Apponix Certified Professional”

Yes, we provide you the assured placement. we have a dedicated team for placement assistance.
 

 All our trainers are working professional having more than 6 years of relevant industry experience.

Our Recent Placements

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Advanced Certificate from JainX - The Skilling Academy of JAIN University

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  •  Use project files and quizzes to practice while you learn
  •  Learn from industry experts who are passionate about teaching

Data science course is best suited for

Fresh Gradutes and Professionals like –

  • Banking and Finance Professionals
  • IT Professionals
  • Analytics Managers
  • Business Analysts
  • Marketing Managers
  • Supply Chain Network Managers
  • Graduates with a Bachelors's or Master’s degree – are the ideal candidates for this course.
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