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Become A Data Scientist Course (Bundle)

Solve real business problems using Data Science

Get Started with Python, Master the Machine Learning Algorithms and Learn the Latest Deep Learning Technologies like Keras & Tensorflow

Upon completion of this course, you will be able to:

  • Get a good grasp on machine learning and deep learning using Python & TensorFlow
  • Understand underlying techniques of data exploration & generate reports
  • Develop machine learning models and build algorithms.

Become

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Talent Gap

LinkedIn reported that there's a shortage of over 151,717 people with data science skills in the U.S

Average Salary

Entry Level (0-3 years) - US$ $90k-113k
Mid-level (3-5 years) - US$ $110-200k

Course Ratings

⭐⭐⭐⭐⭐
        5/5
  1. Python & Basic Statistics

    Programming, Data Handling, Plots, Cleaning.

  2. Machine Learning with Python

    Regression, Decision trees, Neural Networks, SVM

  3. Deep Learning

    Keras, Tensolflow, ANN, LSTM, CNN, RNN

Our Students
working in leading companies

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INTRODUCTION

Data Scientist analyses and interprets complex data in order to assist a business in its decision-making. Data Scientist not only identifies underlying problems but also helps the company in identifying untapped opportunities. In other words, data science is the practice of looking for meaning in mass amounts of data. This role runs much deeper than the data analyst role as a data scientist provides insights beyond basic analysis with the help of advanced analytical technologies like machine learning and predictive modeling.

WHAT IS DATA SCIENTIST COURSE?

Data Scientist Course provides training on the technology that is essential to become a certified Data Scientist. You will learn the most in-demand technologies and languages such as R, SAS, and Python and will be able to conduct data analysis, data exploration, and build regression models. With the help of this course, you can develop the skills and knowledge to analyze data in many forms and communicate insights. By the end of this course, you will have a clear understanding of machine learning and deep learning.

About Course Bundle 📖
You'll Learn 👨‍🎓
Eligibility ✅
Why Enroll❓

Data Scientist is an analytical data expert and hence Data Scientist course syllabus covers the latest
analytics tools and techniques along with their business applications. This course will teach you
the technical skills to resolve compound problems and to identify problems that need to be
solved. You will learn to solve business-related issues using data-driven techniques.

Bundle-Name: Become a Data Scientist

Course #1: Python programming for Data Science, [30+ Lessons and 3+ hours]

Course #2: Machine learning with Python [80+ Lessons and 5+hours]

Course #3: Deep learning with Keras and Tensorflow [100+ Lessons and 7+ hours]

Course Instructor: Venkat Reddy Konsani (IIT Bombay)

Author of the book, Practical Business Analytics using SaaS

What will you get in this course?

  • 15+ hours of videos
  • 15 hours of practice assignments
  • 300+ lessons
  • 30 assignments for practicing real-life examples
  • All practice files related to videos
  • Access to all videos 24 x 7 – learn online from anywhere

WHAT YOU WILL BE ABLE TO DO AFTER COMPLETING THIS DATA SCIENTIST COURSE?

Get a good grasp on machine learning and deep learning using Python & TensorFlow

Understand underlying techniques of data exploration & generate reports

Develop machine learning models and build algorithms

Build linear regression models for predicting the counts

Perform customer segmentation tasks

Perform the classification tasks in various domains like Banking, Insurance, E-commerce, Retail and Healthcare

Perform model fine-tuning and selection techniques

Perform model validation

Perform image classification and computer vision tasks

WHO IS ELIGIBLE FOR DATA SCIENCE COURSE?

ARE YOU ANY OF THESE?

Any data science aspirants.

Graduates and undergraduate students from mathematics or statistics background.

Reporting analysts who want to move into data science.

If you’re keen to get Data Science certification.

Anyone who wants to get started with machine learning & deep learning.

Predictive modelers who want to learn machine learning & deep learning.

Data visualization experts who want to get started with machine learning & deep learning.

Computer vision enthusiasts.

Deep learning enthusiasts.

Computer Science Engineering students.

Research scholars who want to perform data analysis in their thesis.

WHY SHOULD I ENROLL IN DATA SCIENCE COURSE?

Abundant lab exercises covering various real business problems.

 The right mix of theory and practical exercises.

Non-mathematicians, non-statisticians and non-programmers can also follow this course.

Industry oriented examples from multiple domains like banking, Insurance, E-commerce, Healthcare, an automobile.

 Created by Industry experts.

 This course teaches you machine learning from the scratch.

Complex concepts are explained using visualizations and analogies to make it easy to understand.

The course also contains assessment and quiz questions.

The course comes with a download link for dataset, codes and sample projects.

WHAT JOBS WILL A DATA SCIENTIST PROGRAM PREPARE ME FOR?

Here are some of the leading data science careers you can choose:

Business Intelligence Dev.

Data Architect

Applications Architect

Cloud Infrastructure Architect

Enterprise Architect

Data Engineer

Machine Learning Scientist

Machine Learning Engineer

Statistician

SURPRISING THINGS YOU CAN DO WITH DATA SCIENCE

WHAT SKILLS YOU WILL GAIN BY TAKING THIS COURSE?

Programming Skills

This course will help you to gain knowledge about programming. Programming skills means knowing the statistical programming languages, like R or Python, and a database querying language like SQL.

Data Wrangling

This course also helps in learning Data Wrangling. Many times, the data you’re analyzing is going to be messy and difficult to work with. Hence, it is really important to know how to deal with imperfections in data using the Data Wrangling technique.

Statistics

Although statistics is important for all types of companies but it becomes a must where stakeholders depend on your help to make well informed decisions and evaluating the experiments

Data Visualization & Communication

Data Visualization and communication is extremely important, especially at new companies that are making data-driven decisions for the first time, or companies that heavily rely on data scientists to make data-driven decisions.

 

Machine Learning

The most important thing that Data Scientist course teaches you is Machine Learning. If you’re at a company with huge amounts of data or at a company where the product is specifically data-driven like Google Maps, in such cases you need to be familiar with machine learning methods.

 

Data Intuition

Data Intuition is also an interesting topic you get to learn in the Data Scientist course. Data Intuition technique helps you to look at the data from all directions and at all levels.

 

Multivariable Calculus & Linear Algebra

Understanding the concepts of Multivariable Calculus and Linear Algebra is most important at companies where the product is defined by the data. Small enhancements in predictive performance or algorithm optimization can lead to huge benefits for the company.

 

Course Instructor

, Become A Data Scientist Online Course

V. Reddy

Data Scientist / Corporate Trainer/ Author

  • 9+ years – Data Scientist / 5+ years – Corporate Training
  • Conducted 5000+ hours training on Data Science and related tools
  • Author of the book “Practical Business Analytics using SAS”
  • Rich industry experience as applied Data Analyst and Data Scientist
  • Experience in credit risk model building, market response model building,
    social media analytics, revenue forecasting and machine learning
  • Post Graduate in Applied Statistics and Informatics from IIT Bombay

Our classes are taught by the industry’s best Instructor, a proven expert in the field of Data Science & Deep Learning.

He has also published a book on SAS & here’s what people have to say about it:

⭐⭐⭐⭐

This book is very good for beginners to understand the Statistical concepts and SAS basics. The author presented material in very descriptive approach and ensured all the examples for the problems described for each concept.

I would recommend this book for the beginners who want to understand the practical business applications.

⭐⭐⭐⭐⭐

This is a great guide for someone who is new to SAS. The book contains many worked out examples with dataset provided within. One can easily master statistical modeling using SAS using this book, in less than a month. The authors have used examples from diverse industries like CPG, Financial services, manufacturing, etc. Great buy and is highly recommended!

 
 

⭐⭐⭐⭐⭐

It’s a very good book for beginners. The book is great for anyone who would like to learn SAS with Analytics for the first time. It provides clear and simple example so that the reader could learn SAS with analytics step by step. After reading this book, I have got good understanding of usage of Analytics with base SAS. The example datasets and codes provide a good hand-on-experience, makes learning easy.

 

Are You Interested?

More than 450+ People have shown interest in this course

BUNDLE COURSE

A comprehensive selection of the Top Data Science and Machine Learning courses, to help you nail your Dream Job in the Data Science field.

, Become A Data Scientist Online Course

, Become A Data Scientist Online Course

, Become A Data Scientist Online Course

Checkout the course outline below

Here is the road map from Zero to Data Scientist

Part 1. Python Programming for Data Science

Module 1: Introduction to Python Programming
This section focuses on getting familiar to Python Environment:


✔️ Introduction to Python programming
✔️ Python Environment and Basic Commands
✔️ Python Objects
✔️ Python Packages and how to install them

Module 2: Data Handling in Python
How to Import and Manipulate the data in Python


✔️ Importing data
✔️ Sampling
✔️ Data Exploration
✔️ Creating Calculated Fields
✔️ Removing Duplicates
✔️ Joining and Merging

Module 3: Basic Statistics and Plots
Understanding Basics Statistics and Graphs to Get Started:


✔️ Measures of Central Tendency
✔️ Measures of Dispersion
✔️ Percentiles and Quartiles
✔️ Box Plots and outlier detection
✔️ Creating Graphs and reporting

Module 4: Data Cleaning and Treatment
How the Modeling Cycle Works and how to Clean the data for Model Building


✔️ Data Exploration
✔️ Cleaning the Data
✔️ Filling the Missing Values
✔️ Finding Outliers and replacing them

Part 2. Machine Learning with Python

Module 5: Linear Regression
You’ll learn about :


✔️ Correlation
✔️ Simple Regression Models
✔️ R-square
✔️ Multiple Regression
✔️ Multicollinearity
✔️ Individual Variable Impact

Module 6: Logistic Regression
You’ll learn about:


✔️ The need for Logistic Regression
✔️ Logistic Regression Models
✔️ Validation of Logistic Regression Models
✔️ Multicollinearity in Logistic Regression
✔️ Individual Impact of Variables
✔️ Confusion Matrix

Module 7: Decision Trees
You’ll learn :


✔️ Segmentation
✔️ Entropy
✔️ Building Decision Trees
✔️ Validation of Trees
✔️ Pruning the trees
✔️ Fine Tuning and Predictions Using Trees

Module 8: Model Selection and Cross-Validation
You’ll learn about:


✔️ How to validate a model
✔️ What is Best Model
✔️ Types of data
✔️ Types of error
✔️ The Problem of Overfitting
✔️ The Problem of underfitting
✔️ Bias-Variance Tradeoff
✔️ Cross-validation
✔️ Boot Strapping

Module 9: Neural Networks
You’ll learn about :


✔️ Neural Networks Intuitions
✔️ Neural networks and vocabulary
✔️ Neural Network Algorithms
✔️ Building the neural networks
✔️ Validating the Neural Network Model
✔️ Neural network Applications
✔️ Image Recognition using Neural Networks

Module 10: SVM
You’ll learn about :


✔️ Introduction
✔️ The decision Boundary with the largest margin
✔️ SVM- The Large Margin Classifier
✔️ SVM Algorithm
✔️ The Kernal Trick
✔️ Building SVM Model
✔️ Conclusion

 

Module 11: Random Forest and Boosting
You’ll learn about :


✔️ Introduction
✔️ Ensemble Learning
✔️ Bagging
✔️ Building Bagging Models
✔️ Random Forest Models
✔️ Building Random Forest Models
✔️ Boosting Algorithms
✔️ Building Boosting models
✔️ Conclusion

Part 3: Deep Learning with TensorFlow and Keras

Module 12: Machine Learning Basics
This section focuses on the Machine Learning prerequisites for Deep Learning:


✔️ Basics of Linear Regression
✔️ Basics of Logistic Regression
✔️ Model Validation Matrices
✔️ Model Selection and Cross-Validation

Module 13: Artificial Neural Networks – Introduction
How to Import and Manipulate the data in Python:


✔️ Neural network Intuition
✔️ Neural network and vocabulary
✔️ Neural network algorithm
✔️ The math behind the neural network algorithm
✔️ Building the neural networks
✔️ Validating the neural network model
✔️ Neural network applications
✔️ Image recognition using neural networks(MNIST)

Module 14: TensorFlow and Keras
Understanding the Basics of the Deep Learning Frameworks:


✔️ Deep Learning frameworks
✔️ What is TensorFlow
✔️ Key terms in TensorFlow
✔️ Working with TensorFlow
✔️ Regression Model building with TensorFlow
✔️ MNIST on Tensorflow
✔️ Keras Introduction
✔️ Keras Advantages
✔️ Working with Keras
✔️ MNIST on Keras

Module 15: ANN Hyper Parameters
Understanding the effect of all the Hyper Parameters used in an ANN model and their Effects:


✔️ Overfitting
✔️ L1 and L2 Regularization
✔️ Dropout
✔️ Activation functions
✔️ Learning Rate
✔️ Momentum
✔️ SGD
✔️ Batch size

 

Module 16: Convolutional Neural Networks
Understanding What are CNN and how we reached to the intuition of CNN’s:


✔️ Building Deep ANN models on Large Datasets
✔️ ANN shortcomings
✔️ CNN Introduction
✔️ Convolution Layer
✔️ Pooling
✔️ CNN Theory
✔️ CNN Implementation
✔️ Building a CNN model to solve the Image Detection Problem

 

Module 17: Recurrent Neural Network(RNN)
How to build a neural network for sequential kind of datasets:


✔️ Why ANN doesn’t work on sequential data/time series kind of data
✔️ Building an intuitive sequential model
✔️ Sequential Models
✔️ RNN Introduction
✔️ Back Propagation Through Time
✔️ RNN Model Building for text prediction
✔️ The problem of Vanishing Gradients

Module 18: Long Short Term Memory(LSTM)
In this session we will try to see the shortcomings of RNN models and how to improve upon it to create a whole new algorithm:


✔️ Vanishing gradients in RNN
✔️ LSTM idea and intuition
✔️ Gates in LSTM/ information flow
✔️ LSTM representation
✔️ Back Propagation in LSTM
✔️ Building LSTM model to overcome the shortcomings of RNN

 

Final Module: Graduation
Course Completion Certificate


 

Ready to get started?

All set to gain Expertise in Data Scientist? Master this “Become A Data Scientist ” bundle Course

BECOME A DATA SCIENTIST

Be A Certified Data Scientist
$200
  • 20+ Hours Of Videos
  • 15+ Hours assignment Practice
  • 300+ Lessons
  • 200+ Video Lessons
  • 24*7 Annual Access
  • 30 assignments for Practising
  • Downloadable Sample Files
Get Instant Access

 
 
 
 
 

What Student’s Say?

Hello Everyone
I am basically from non-Analytics background. With an appetite to move into Analytics, I looked out for a suitable material that helps me to build on. Fortunately, I got this source. And, after going thru the brief intro, I identified that this one will definitely help. To my surprise, post I got it, when I flipped thru diff topics, I was amazed at the ease the author provided a deep insight about each topic. All the examples given were indeed relevant and increased my confidence. I certainly refer this book to amateurs who want to pursue their careers into Analytics.

Super book for people making start in Analytics…

Concepts illustrated with clarity with good examples and steps.

Overall Very good book

safe_checkout1

BECOME A DATA SCIENTIST

Be A Certified Data Scientist
₹ 14,000
  • 20+ Hours Of Videos
  • 15+ Hours assignment Practice
  • 300+ Lessons
  • 200+ Video Lessons
  • 24*7 Annual Access
  • 30 assignments for Practising
  • Downloadable Sample Files
Get Instant Access

 
 
 
 
 

What Student’s Say?

Hello Everyone
I am basically from non-Analytics background. With an appetite to move into Analytics, I looked out for a suitable material that helps me to build on. Fortunately, I got this source. And, after going thru the brief intro, I identified that this one will definitely help. To my surprise, post I got it, when I flipped thru diff topics, I was amazed at the ease the author provided a deep insight about each topic. All the examples given were indeed relevant and increased my confidence. I certainly refer this book to amateurs who want to pursue their careers into Analytics.

Super book for people making start in Analytics…

Concepts illustrated with clarity with good examples and steps.

Overall Very good book

safe_checkout1

certification of data scientist

Unlock your completion certificate

  • Complete any premium course at Yoda Learning Solutions
  • You are awarded a completion diploma
  • The diploma can be verified via URL and exported to LinkedIn to boost your career and impress potential employers.

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Frequently Asked Questions

FAQ

HOW CAN I BECOME A DATA SCIENTIST?

In order to learn Data Science and become a data scientist, you must know various programming languages like SAS, R and Python and also should have a good knowledge of statistics and mathematics. After learning these skills, you can easily become a Data Scientist. To learn SAS, you can take our SAS programming course.

WHAT SHOULD I DO TO LEARN LESSONS EASILY?

You should know the basic coding fundamentals.
Strong internet connection is required.
You should have basic Computer Skills.
You should have logical thinking.
You should be keen to learn.
You should have Basic Math Skills.
You should have Basic Stats Skills.

WHAT TO DO IF I’VE GOT QUESTIONS OR DOUBTS?

Once you opt for any Course from Yoda Learning, you get Lifetime Support. You can go through the Video Tutorials as many times as you wish and shoot us your questions and doubts whenever you want. We have the best instructors with us who have vast experience in this field and will answer your questions as soon as possible.

WHAT HAPPENS WHEN I’M DONE VIEWING ALL THE LESSONS?

Once you’re done viewing the Data Science tutorial from Yoda Learning, you can watch it again. Once you enroll in any Online Course from Yoda Learning, you can view it at your leisure hours and feel free to repeat the lessons and ask questions and doubts if you have got any.

DOES DATA SCIENTIST COURSE OFFER PRICE VALUE?

Data Science online Course from Yoda Learning is one of the best Data Science courses and will offer you greater value. It’s reasonably priced and has the power to take your career to the next level. As a Data Scientist, you get the opportunity to work for a wide range of companies because you will be coming up with solutions and information related to customer retainment, marketing solutions, new products or general business solutions. So suffice it to say, it offers great value for money.

DO WE GET THE COURSE COMPLETION CERTIFICATE?

Once you have completed the “Become A Data Scientist course”, you’ll be getting a Course Completion Certificate which is LinkedIn Verified. You can use it to grab better Job Opportunities.

WHAT IF I'VE GOT A DOUBT IN ANY OF THE SECTIONS FROM THE MODULE?

You get the Support from the industry Experts and our Course instructors in case you’ve got a doubt about anything related to the course.