Data Science, Machine Learning, Deep Learning and Artificial Intelligence

Introduction to Data Science, Machine Learning, Deep Learning and Artificial Intelligence  Basics of Python and Hands-on on Python  Introduction to Data Science using Python  Hands on session on Data Science with Python [Database Connectivity with PYTHON: Performing Database Transactions (Inserting, Deleting, and Updating the Database)]  Introduction to Machine Learning and its types  Examples Overview of Machine Learning packages in Python  Introduction to Deep Learning and its types  Project in Data Science/Machine Learning /Artificial Intelligence

What you'll do

Learning Outcomes:
 Learn to use Python, to develop Machine learning applications.
 Learn Machine learning methodologies to process not only image based datasets
but also raw text, numbers etc.
 Develop ability to independently solve business problems using Machine learning
 Develop a verified portfolio with hands on Machine learning projects that will
showcase the new skills acquired to employers.

Outcomes of the Program
1. Participants will be able to gain an overview of Data science, Machine Learning,
Deep Learning and Artificial Intelligence.
2. Participants will be able to code using Python.
3. Participants will be able to understand Data science concepts like Data analysis,
Data interpretation and Data visualization.
4. Participants will be able to understand Basics of (EDA) Exploratory Data Analysis.
5. Participants will able to work with Machine Learning and its applications.
6. Participants will able to work with Machine Learning.

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From $149
15-June-2021 $149

What You Will Learn

Chapter 1: Regression Analysis

1. Simple Linear Regression
2. Multiple Linear Regression
3. Polynomial Regression
4. Advanced Regression
Chapter 2: Classification Methods

1.Logistic Regression
2. Naïve Bayes
3. KNN
4.Support Vector Machines (SVM)
5.Decision Tree
6.Random Forest

Chapter 3: Bootstrap Aggregation (Bagging) Ensemble Learning
Chapter 4: Boosting Ensemble Learning
Chapter 5: Stacking and Blending Ensemble Learning

Chapter 6: Clustering Techniques
 K-means Clustering
 Hierarchical Clustering
 DBSCAN Clustering
 Bert Clustering etc

Chapter 7: Dimensionality Reduction-
 Principal Component Analysis (PCA)
 Linear Discriminative Analysis (LDA)

Chapter 8: Associate Rule
 Aproiri Algorithm
 FP Growth

Chapter 9: Recommendation system
 Popularity Based Recommendation System
 Market Basket Recommendation System
 Content Based Recommendation
 Collaborative Recommendation
 Hybrid recommendation systems

Chapter 10: Cross Validation Techniques
 Exhaustive CV
 Non Exhaustive CV
 Rolling Cross Validation

Chapter 11: Model selection and Tuning

Chapter 12: Model Performance and Measure (Evaluation Metrics)
 Regression Evaluation Metrics
 Classification Evaluation Metrics

Chapter 13: Model Regularization Method
Chapter 14: Model Hyperparameter Optimization
Chapter 15: ML Pipeline

Chapter 16: Value Based Methods: Q Learning
Chapter 17: SARSA

Chapter 18: Model Deployment through Cloud Computing
 Amazon web services (AWS)
 Microsoft Azure (MA)
 Google Cloud Platform (GCP)
 Flask
 Hereku

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What You Will Get

Platforms & Tools

How does it work

How does it work

To assist you in identifying your goals and help achieve them.

What will be assessed?

  • Goals
  • Skill Rating
  • Ongoing assessment to meet your objectives.

Externship refers to virtual employment. Avail this modern trend in employment. Join real companies and become their virtual employee. Solve real problems, get hands-on real-time experience, assess your gaps and then either get the same job or other curated opportunities.

What will you receive?

  • Virtual Employment
  • Portfolio - it can be showcased with your CV

While enactment, you will realize your skill gaps and struggles which then can be explored. You can explore various skills and attend live masterclasses from experts and doubt clearing sessions to meet those gaps.

What will you receive?

  • Online Live masterclasses
  • Live Coaching.
  • Doubt Clearing

Experience comes in the form of job assistance services, mentorship or even getting connected with on-field experts who help you achieve your career goals.

What will you receive?

  • Job Assistance*



Career assistance service to fina a suitable opportunituy - Resume writing, Interview Coaching

Meet Your Instructor

Arpit Yadav
Data Science, Machine Learning, Deep Learning and Artificial Intelligence

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About Education:
• Pursuing Phd in Machine Learning from SVVV, Indore.
• PGP in Artificial Intelligence and Machine Learning from University at Texas at Austin , USA
• M.Tech (VLSI Design) from GHRCE, Nagpur.
• B.E (Electronics and Telecommunication) from JDIET, Yavatmal.

About Achievements:
1. VDGOOD Inspirational Scientist Award in the 7th International Scientist Awards on Engineering, Science and Medicine.
2. Awarded as Excellence in Research (HEI Awards) THE PROGRESS GLOBAL AWARD 2020.
3. Awarded as Best in Innovation, Training and Design Award of “International Association of Educators and Corporate Trainers –IAECT Award 2020”.
4. Awarded as “Best Corporate Trainer Award of “International Association of Educators and Corporate Trainers –IAECT Award 2020”.

I am working as Artificial intelligence and Machine Learning Researcher at tensorBrew, Hyderabad. I am also working as Freelancer Corporate Trainer in Python, Data Science, Machine Learning, Deep Learning, and Artificial Intelligence. I am currently pursuing Ph. D in Machine Learning from SVVV Indore. I have done done PGP in Artificial Intelligence and Machine Learning from Great Lakes, Hyderabad. I have done M.Tech in VLSI Design and B. E in Electronics & Telecommunication Engineering. I am having having 11 Years of Experience in VLSI Research, Machine Learning, Data Science and Artificial Intelligence.
I have done 70+ Certifications in the domain of Data Science, Machine Learning, Deep Learning and Artificial Intelligence. I have conducted many sessions on Data Science , Machine Learning and Artificial Intelligence across India. My other skills include Aptitude Development, Group Discussion, Extempore/Elocution/Debates, Counseling, Motivational Talk, Resume, Writing ,Video Resume Cover Letter ,Expert Talks,Personal Interview/Technical Interview. I am also Giving Training to Competitive Examination/ CRT (Campus Recruitment Training).

Core Skills:

· Tools: Python, VHDL, VLSI Design, Keras, TensorFlow, OpenCV, NLTK.

· Skills: Data Science Using Python, Machine Learning Using Python, Data Analysis, Data Visualization, Deep Learning, Neural Network, Natural Language Processing (NLP), Computer Vision(CV).

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Learner's Project

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